Analyze_William.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "unzip_path = \"./dataset/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset extracted to \"/Users/williamhutchinson/Local_Docs/SEM1_Coding/ML/ML_Hackathon/ml_hackathon/dataset\"\n"
     ]
    },
    {
     "data": {
      "text/plain": "   Wohngebiet Nachbarschaft Bedingung1 Bedingung2  Wohnungsklasse Gebauedetyp  \\\nId                                                                              \n1          WN        Gallus       Norm       Norm              20        1Fam   \n2          WN        Gallus       Norm       Norm              20        1Fam   \n3          WN       Eckenhe       Norm       Norm              50        1Fam   \n4          WN       Ginnhei       Norm       Norm              60        1Fam   \n5          WN       Eckenhe       Norm       Norm              70        1Fam   \n\n   Wohnungsstil  Baujahr  Umbaujahr  Hausqualitaet  ...  Garagenqualitaet  \\\nId                                                  ...                     \n1          1Sto     1962       1962              3  ...                Du   \n2          1Sto     2015       2016              5  ...                Du   \n3          2Sto     1930       1960              6  ...                Du   \n4          2Sto     2009       2010              6  ...                Du   \n5          2Sto     1939       1960              8  ...                Du   \n\n   Garagenzustand  EinfahrtGepflastert Sondermerkmal SondermerkmalWert  \\\nId                                                                       \n1              Ar                    J           NaN               0.0   \n2              Du                    J           NaN               0.0   \n3              Du                    P           NaN               0.0   \n4              Du                    J           NaN               0.0   \n5              Du                    J           NaN               0.0   \n\n   Verkaufsmonat Verkaufsjahr  Verkaufstyp Verkaufsbedingung Verkaufspreis  \nId                                                                          \n1              7         2019         GarK            Normal       69700.0  \n2              6         2017         GarK            Normal      133450.0  \n3              9         2016         GarK            Normal      165750.0  \n4              5         2017         GarK            Normal      157250.0  \n5              6         2016         GarK            Normal      195500.0  \n\n[5 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Wohngebiet</th>\n      <th>Nachbarschaft</th>\n      <th>Bedingung1</th>\n      <th>Bedingung2</th>\n      <th>Wohnungsklasse</th>\n      <th>Gebauedetyp</th>\n      <th>Wohnungsstil</th>\n      <th>Baujahr</th>\n      <th>Umbaujahr</th>\n      <th>Hausqualitaet</th>\n      <th>...</th>\n      <th>Garagenqualitaet</th>\n      <th>Garagenzustand</th>\n      <th>EinfahrtGepflastert</th>\n      <th>Sondermerkmal</th>\n      <th>SondermerkmalWert</th>\n      <th>Verkaufsmonat</th>\n      <th>Verkaufsjahr</th>\n      <th>Verkaufstyp</th>\n      <th>Verkaufsbedingung</th>\n      <th>Verkaufspreis</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>WN</td>\n      <td>Gallus</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>20</td>\n      <td>1Fam</td>\n      <td>1Sto</td>\n      <td>1962</td>\n      <td>1962</td>\n      <td>3</td>\n      <td>...</td>\n      <td>Du</td>\n      <td>Ar</td>\n      <td>J</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>7</td>\n      <td>2019</td>\n      <td>GarK</td>\n      <td>Normal</td>\n      <td>69700.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>WN</td>\n      <td>Gallus</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>20</td>\n      <td>1Fam</td>\n      <td>1Sto</td>\n      <td>2015</td>\n      <td>2016</td>\n      <td>5</td>\n      <td>...</td>\n      <td>Du</td>\n      <td>Du</td>\n      <td>J</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>6</td>\n      <td>2017</td>\n      <td>GarK</td>\n      <td>Normal</td>\n      <td>133450.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>WN</td>\n      <td>Eckenhe</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>50</td>\n      <td>1Fam</td>\n      <td>2Sto</td>\n      <td>1930</td>\n      <td>1960</td>\n      <td>6</td>\n      <td>...</td>\n      <td>Du</td>\n      <td>Du</td>\n      <td>P</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>9</td>\n      <td>2016</td>\n      <td>GarK</td>\n      <td>Normal</td>\n      <td>165750.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>WN</td>\n      <td>Ginnhei</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>60</td>\n      <td>1Fam</td>\n      <td>2Sto</td>\n      <td>2009</td>\n      <td>2010</td>\n      <td>6</td>\n      <td>...</td>\n      <td>Du</td>\n      <td>Du</td>\n      <td>J</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>5</td>\n      <td>2017</td>\n      <td>GarK</td>\n      <td>Normal</td>\n      <td>157250.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>WN</td>\n      <td>Eckenhe</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>70</td>\n      <td>1Fam</td>\n      <td>2Sto</td>\n      <td>1939</td>\n      <td>1960</td>\n      <td>8</td>\n      <td>...</td>\n      <td>Du</td>\n      <td>Du</td>\n      <td>J</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>6</td>\n      <td>2016</td>\n      <td>GarK</td>\n      <td>Normal</td>\n      <td>195500.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from io import BytesIO\n",
    "from urllib.request import urlopen\n",
    "from zipfile import ZipFile\n",
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "# data_url = \"https://dshare.mathematik.uni-marburg.de/index.php/s/GrPtczNmDZQcn9f/download/training_dataset.zip\"\n",
    "\n",
    "# with urlopen(data_url) as zipresp:\n",
    "#     with ZipFile(BytesIO(zipresp.read())) as zfile:\n",
    "#         zfile.extractall(unzip_path)\n",
    "\n",
    "print('Dataset extracted to \"{:s}\"'.format(os.path.realpath(unzip_path)))\n",
    "df = pd.read_csv('dataset/train.csv', index_col='Id')\n",
    "df.head(5)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [],
   "source": [
    "features = df.columns[:-1]\n",
    "features_20_1, features_20_2, features_20_3, features_19_4 = features[:20], features[20:40], features[40:60], features[60:]\n",
    "\n",
    "df_20_1 = pd.concat([df[features_20_1], df['Verkaufspreis']], axis=1)\n",
    "df_20_2 = pd.concat([df[features_20_2], df['Verkaufspreis']], axis=1)\n",
    "df_20_3 = pd.concat([df[features_20_3], df['Verkaufspreis']], axis=1)\n",
    "df_20_4 = pd.concat([df[features_19_4], df['Verkaufspreis']], axis=1)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "        OberirdischeWohnflaeche  1Stockflaeche  2Stockflaeche  \\\ncount               2000.000000    2000.000000    2000.000000   \nunique                      NaN            NaN            NaN   \ntop                         NaN            NaN            NaN   \nfreq                        NaN            NaN            NaN   \nmean                 135.531945     104.294025      30.785310   \nstd                   46.068902      35.585721      38.841752   \nmin                   36.630000      36.630000       0.000000   \n25%                  101.767500      78.907500       0.000000   \n50%                  129.645000      97.290000       0.000000   \n75%                  156.442500     124.380000      63.360000   \nmax                  507.780000     458.550000     185.850000   \n\n        GeringequalitaetFlaeche  OberirdischeRaueme Funktionalitaet  \\\ncount                2000.00000         2000.000000            1998   \nunique                      NaN                 NaN               7   \ntop                         NaN                 NaN             Typ   \nfreq                        NaN                 NaN            1864   \nmean                    0.45261            6.466000             NaN   \nstd                     4.32349            1.558223             NaN   \nmin                     0.00000            3.000000             NaN   \n25%                     0.00000            5.000000             NaN   \n50%                     0.00000            6.000000             NaN   \n75%                     0.00000            7.000000             NaN   \nmax                    95.76000           15.000000             NaN   \n\n        OberirdischeVollbadezimmer  OberirdischeHalbbadezimmer  Schlafzimmer  \\\ncount                  2000.000000                 2000.000000   2000.000000   \nunique                         NaN                         NaN           NaN   \ntop                            NaN                         NaN           NaN   \nfreq                           NaN                         NaN           NaN   \nmean                      1.572000                    0.378000      2.867500   \nstd                       0.548604                    0.498237      0.815645   \nmin                       0.000000                    0.000000      0.000000   \n25%                       1.000000                    0.000000      2.000000   \n50%                       2.000000                    0.000000      3.000000   \n75%                       2.000000                    1.000000      3.000000   \nmax                       4.000000                    2.000000      8.000000   \n\n            Kuechen KuechenQualitaet       Kamine Kaminqualitaet Heizung  \\\ncount   2000.000000             1999  2000.000000           1040    2000   \nunique          NaN                4          NaN              5       5   \ntop             NaN               Du          NaN             Gu   GasWO   \nfreq            NaN             1034          NaN            527    1971   \nmean       1.042500              NaN     0.603500            NaN     NaN   \nstd        0.204242              NaN     0.647686            NaN     NaN   \nmin        1.000000              NaN     0.000000            NaN     NaN   \n25%        1.000000              NaN     0.000000            NaN     NaN   \n50%        1.000000              NaN     1.000000            NaN     NaN   \n75%        1.000000              NaN     1.000000            NaN     NaN   \nmax        3.000000              NaN     4.000000            NaN     NaN   \n\n       Heizungsqualitaet Klimalanlage Elektrik  Holzdeckflaeche  \\\ncount               2000         2000     1999      2000.000000   \nunique                 5            2        5              NaN   \ntop                   Ag            J    SLSRo              NaN   \nfreq                1024         1865     1827              NaN   \nmean                 NaN          NaN      NaN         8.575200   \nstd                  NaN          NaN      NaN        11.506873   \nmin                  NaN          NaN      NaN         0.000000   \n25%                  NaN          NaN      NaN         0.000000   \n50%                  NaN          NaN      NaN         0.000000   \n75%                  NaN          NaN      NaN        15.120000   \nmax                  NaN          NaN      NaN       128.160000   \n\n        OffeneVerandaflaeche  GeschlosseneVerandaflaeche  Verkaufspreis  \ncount            2000.000000                 2000.000000     2000.00000  \nunique                   NaN                         NaN            NaN  \ntop                      NaN                         NaN            NaN  \nfreq                     NaN                         NaN            NaN  \nmean                4.269735                    2.126205   153708.42060  \nstd                 5.952831                    6.010000    68822.30926  \nmin                 0.000000                    0.000000    10870.65000  \n25%                 0.000000                    0.000000   109650.00000  \n50%                 2.430000                    0.000000   136000.00000  \n75%                 6.300000                    0.000000   181475.00000  \nmax                51.300000                   91.080000   641750.00000  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>GeringequalitaetFlaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>Funktionalitaet</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>KuechenQualitaet</th>\n      <th>Kamine</th>\n      <th>Kaminqualitaet</th>\n      <th>Heizung</th>\n      <th>Heizungsqualitaet</th>\n      <th>Klimalanlage</th>\n      <th>Elektrik</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>2000.000000</td>\n      <td>2000.000000</td>\n      <td>2000.000000</td>\n      <td>2000.00000</td>\n      <td>2000.000000</td>\n      <td>1998</td>\n      <td>2000.000000</td>\n      <td>2000.000000</td>\n      <td>2000.000000</td>\n      <td>2000.000000</td>\n      <td>1999</td>\n      <td>2000.000000</td>\n      <td>1040</td>\n      <td>2000</td>\n      <td>2000</td>\n      <td>2000</td>\n      <td>1999</td>\n      <td>2000.000000</td>\n      <td>2000.000000</td>\n      <td>2000.000000</td>\n      <td>2000.00000</td>\n    </tr>\n    <tr>\n      <th>unique</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4</td>\n      <td>NaN</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>5</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>top</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Typ</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Du</td>\n      <td>NaN</td>\n      <td>Gu</td>\n      <td>GasWO</td>\n      <td>Ag</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>freq</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1864</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1034</td>\n      <td>NaN</td>\n      <td>527</td>\n      <td>1971</td>\n      <td>1024</td>\n      <td>1865</td>\n      <td>1827</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>135.531945</td>\n      <td>104.294025</td>\n      <td>30.785310</td>\n      <td>0.45261</td>\n      <td>6.466000</td>\n      <td>NaN</td>\n      <td>1.572000</td>\n      <td>0.378000</td>\n      <td>2.867500</td>\n      <td>1.042500</td>\n      <td>NaN</td>\n      <td>0.603500</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>8.575200</td>\n      <td>4.269735</td>\n      <td>2.126205</td>\n      <td>153708.42060</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>46.068902</td>\n      <td>35.585721</td>\n      <td>38.841752</td>\n      <td>4.32349</td>\n      <td>1.558223</td>\n      <td>NaN</td>\n      <td>0.548604</td>\n      <td>0.498237</td>\n      <td>0.815645</td>\n      <td>0.204242</td>\n      <td>NaN</td>\n      <td>0.647686</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>11.506873</td>\n      <td>5.952831</td>\n      <td>6.010000</td>\n      <td>68822.30926</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>36.630000</td>\n      <td>36.630000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>3.000000</td>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>1.000000</td>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>10870.65000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>101.767500</td>\n      <td>78.907500</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>5.000000</td>\n      <td>NaN</td>\n      <td>1.000000</td>\n      <td>0.000000</td>\n      <td>2.000000</td>\n      <td>1.000000</td>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>109650.00000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>129.645000</td>\n      <td>97.290000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>6.000000</td>\n      <td>NaN</td>\n      <td>2.000000</td>\n      <td>0.000000</td>\n      <td>3.000000</td>\n      <td>1.000000</td>\n      <td>NaN</td>\n      <td>1.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>2.430000</td>\n      <td>0.000000</td>\n      <td>136000.00000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>156.442500</td>\n      <td>124.380000</td>\n      <td>63.360000</td>\n      <td>0.00000</td>\n      <td>7.000000</td>\n      <td>NaN</td>\n      <td>2.000000</td>\n      <td>1.000000</td>\n      <td>3.000000</td>\n      <td>1.000000</td>\n      <td>NaN</td>\n      <td>1.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>15.120000</td>\n      <td>6.300000</td>\n      <td>0.000000</td>\n      <td>181475.00000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>507.780000</td>\n      <td>458.550000</td>\n      <td>185.850000</td>\n      <td>95.76000</td>\n      <td>15.000000</td>\n      <td>NaN</td>\n      <td>4.000000</td>\n      <td>2.000000</td>\n      <td>8.000000</td>\n      <td>3.000000</td>\n      <td>NaN</td>\n      <td>4.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>128.160000</td>\n      <td>51.300000</td>\n      <td>91.080000</td>\n      <td>641750.00000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.max_rows = 85\n",
    "pd.options.display.max_columns = 85\n",
    "df_20_3.describe(include='all')"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# Analyze William\n",
    "\n",
    "## Oberirdirsche Wohnflaeche"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "OberirdischeWohnflaeche: Oberirdische Wohnfläche in Quadratmetern\n",
    "\n",
    "1Stockflaeche: Größe des ersten Stocks in Quadratmetern\n",
    "\n",
    "2Stockflaeche: Größe des zweiten Stocks in Quadratmetern\n",
    "\n",
    "GeringequalitaetFlaeche: Größe ausgebauter Bereich in geringer Qualität in Quadratmetern (alle Stockwerke)\n",
    "\n",
    "OberirdischeRaueme: Gesamtzahl der oberirdischen Räume (ohne Badezimmer)\n",
    "\n",
    "Funktionalitaet: Wohnfunktionalität (Annahme typisch, sofern keine Abzüge gerechtfertigt sind)\n",
    "\n",
    "       Typ\tTypische Funktionalität\n",
    "       Ger1\tGeringfügige Abzüge 1\n",
    "       Ger2\tGeringfügige Abzüge 2\n",
    "       Mit\tMittlere Abzüge\n",
    "       Gro1\tGroße Abzüge 1\n",
    "       Gro2\tGroße Abzüge 2\n",
    "       Sch\tSchwere Beschädigungen\n",
    "       Ber\tNur Bergung\n",
    "\n",
    "OberirdischeVollbadezimmer: Oberirdische vollständige Badezimmer\n",
    "\n",
    "OberirdischeHalbbadezimmer: Oberirdische halbe Badezimmer\n",
    "\n",
    "Schlafzimmer: Oberirdische Schlafzimmer (umfasst NICHT Schlafzimmer im Keller)\n",
    "\n",
    "Kuechen: Oberirdische Küchen\n",
    "\n",
    "KuechenQualitaet: Qualität der Küchen\n",
    "\n",
    "       Ag\tAusgezeichnet\n",
    "       Gu\tGut\n",
    "       Du\tDurchschnittlich/Typisch\n",
    "       Ar\tAusreichend\n",
    "       Sc\tSchlecht\n",
    "\n",
    "Kamine: Anzahl der Kamine\n",
    "\n",
    "Kaminqualitaet: Qualität der Kamine\n",
    "\n",
    "       Ag\tAusgezeichnet\n",
    "       Gu\tGut\n",
    "       Du\tDurchschnittlich/Typisch\n",
    "       Ar\tAusreichend\n",
    "       Sc\tSchlecht\n",
    "       NA\tKeine Kamine\n",
    "\n",
    "Heizung: Art der Heizung\n",
    "\n",
    "       BodOf\tFußbodenofen\n",
    "       GasWO\tGasbefeuerter Warmluftofen\n",
    "       GasWD\tGasbetriebene Warmwasser- oder Dampfheizung\n",
    "       GravOf\tGravitationsofen\n",
    "       NGasWD\tNicht Gasbetriebene Warmwasser- oder Dampfheizung\n",
    "       WandOf\tWandofen\n",
    "\n",
    "Heizungsqualitaet: Heizungsqualität und -zustand\n",
    "\n",
    "       Ag\tAusgezeichnet\n",
    "       Gu\tGut\n",
    "       Du\tDurchschnittlich/Typisch\n",
    "       Ar\tAusreichend\n",
    "       Sc\tSchlecht\n",
    "\n",
    "Klimalanlage: Zentrale Klimaanlage\n",
    "\n",
    "       N\tNein\n",
    "       J\tJa\n",
    "\n",
    "Elektrik: Elektrische Anlage\n",
    "\n",
    "       SLSRo\tStandard-Leistungsschalter & Romex-Verkabelung\n",
    "       SichDu\tSicherungskasten mit über 60 AMP und vollständige Romex-Verkabelung (Durchschnitt)\n",
    "       SichAr\t60 AMP-Sicherungskasten und überwiegend Romex-Verkabelung (Ausreichend)\n",
    "       SichSc\t60-AMP-Sicherungskasten und meist Knopf- und Röhrenverkabelung (schlecht)\n",
    "       Mix\t\tGemischt\n",
    "\n",
    "Holzdeckflaeche: Fläche des Holzdecks in Quadratmetern\n",
    "\n",
    "OffeneVerandaflaeche: Offener Verandabereich in Quadratmetern\n",
    "\n",
    "GeschlosseneVerandaflaeche: Geschlossener Verandabereich in Quadratmetern"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Feature Analysis"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Missing Values:\n",
      "OberirdischeWohnflaeche         0\n",
      "1Stockflaeche                   0\n",
      "2Stockflaeche                   0\n",
      "GeringequalitaetFlaeche         0\n",
      "OberirdischeRaueme              0\n",
      "Funktionalitaet                 2\n",
      "OberirdischeVollbadezimmer      0\n",
      "OberirdischeHalbbadezimmer      0\n",
      "Schlafzimmer                    0\n",
      "Kuechen                         0\n",
      "KuechenQualitaet                1\n",
      "Kamine                          0\n",
      "Kaminqualitaet                960\n",
      "Heizung                         0\n",
      "Heizungsqualitaet               0\n",
      "Klimalanlage                    0\n",
      "Elektrik                        1\n",
      "Holzdeckflaeche                 0\n",
      "OffeneVerandaflaeche            0\n",
      "GeschlosseneVerandaflaeche      0\n",
      "Verkaufspreis                   0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(\"\\nMissing Values:\")\n",
    "print(df_20_3.isnull().sum())\n",
    "\n",
    "#Funktionalität: 2 NaN (mit Kaminqualitaet NaN)\n",
    "#KuechenQualitaet: 1 NaN (mit Kaminqualitaet NaN)\n",
    "#Kaminqualitaet: 960 NaN (womit korreliert?)\n",
    "#Elektrik: 1 NaN (mit Kaminqualitaet NaN)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows with null values in multiple features (relevant columns only):\n",
      "     Funktionalitaet KuechenQualitaet Kaminqualitaet Elektrik\n",
      "Id                                                           \n",
      "542              NaN               Ar            NaN   SichDu\n",
      "1001             NaN               Du            NaN    SLSRo\n",
      "1144             Mit              NaN            NaN    SLSRo\n",
      "1699             Typ               Gu            NaN      NaN\n"
     ]
    }
   ],
   "source": [
    "# Find rows where multiple features are null\n",
    "rows_with_nulls = df_20_3[df_20_3.isnull().sum(axis=1) > 1]\n",
    "\n",
    "# Display only relevant columns for the rows with null values\n",
    "relevant_columns = df_20_3.columns[df_20_3.isnull().any()]\n",
    "print(\"Rows with null values in multiple features (relevant columns only):\")\n",
    "print(rows_with_nulls[relevant_columns])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Kamine Kaminqualitaet\n",
      "Id                         \n",
      "1          0            NaN\n",
      "2          0            NaN\n",
      "7          0            NaN\n",
      "10         0            NaN\n",
      "14         0            NaN\n",
      "...      ...            ...\n",
      "1989       0            NaN\n",
      "1994       0            NaN\n",
      "1995       0            NaN\n",
      "1996       0            NaN\n",
      "1999       0            NaN\n",
      "\n",
      "[960 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "df_kamin = df_20_3[df_20_3['Kaminqualitaet'].isnull()]\n",
    "selected_columns = ['Kamine','Kaminqualitaet']\n",
    "print(df_kamin.loc[:,selected_columns])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows with null values in multiple features (relevant columns only):\n",
      "     Funktionalitaet KuechenQualitaet Kaminqualitaet Elektrik\n",
      "Id                                                           \n",
      "542              NaN               Ar            NaN   SichDu\n",
      "1001             NaN               Du            NaN    SLSRo\n",
      "1144             Mit              NaN            NaN    SLSRo\n",
      "1699             Typ               Gu            NaN      NaN\n"
     ]
    }
   ],
   "source": [
    "# Find rows where multiple features are null\n",
    "rows_with_nulls = df_20_3[(df_20_3['Kaminqualitaet'].isnull()) & (df_20_3.isnull().sum(axis=1) > 1)]\n",
    "\n",
    "# Display only relevant columns for the rows with null values\n",
    "relevant_columns = df_20_3.columns[df_20_3.isnull().any()]\n",
    "print(\"Rows with null values in multiple features (relevant columns only):\")\n",
    "print(rows_with_nulls[relevant_columns])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Plotting of features"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def plot_feature(df, feature):\n",
    "    plt.figure(figsize=(10, 5))\n",
    "    plt.scatter(df[feature], df['Verkaufspreis'])\n",
    "    plt.xlabel(feature)\n",
    "    plt.ylabel('Verkaufspreis')\n",
    "    plt.show()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "def plot_all_features(df):\n",
    "    plt.figure(figsize=(20, 20))\n",
    "    for i, feature in enumerate(df.columns):\n",
    "        # delete empty values\n",
    "        df = df[df[feature].notnull()]\n",
    "        try:\n",
    "            plt.subplot(5, 4, i+1)\n",
    "            plt.scatter(df[feature], df['Verkaufspreis'])\n",
    "            plt.xlabel(feature)\n",
    "            plt.ylabel('Verkaufspreis')\n",
    "        except Exception as e:\n",
    "            print(e)\n",
    "    plt.show()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "OberirdischeWohnflaeche       1971\n1Stockflaeche                 1971\n2Stockflaeche                 1971\nGeringequalitaetFlaeche       1971\nOberirdischeRaueme            1971\nFunktionalitaet               1970\nOberirdischeVollbadezimmer    1971\nOberirdischeHalbbadezimmer    1971\nSchlafzimmer                  1971\nKuechen                       1971\nKuechenQualitaet              1970\nKamine                        1971\nKaminqualitaet                1031\nHeizung                       1971\nHeizungsqualitaet             1971\nKlimalanlage                  1971\nElektrik                      1970\nHolzdeckflaeche               1971\nOffeneVerandaflaeche          1971\nGeschlosseneVerandaflaeche    1971\nVerkaufspreis                 1971\ndtype: int64"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_20_3[df_20_3[\"Heizung\"] == \"GasWO\"].count()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num must be an integer with 1 <= num <= 20, not 21\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 2000x2000 with 20 Axes>",
      "image/png": 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Q1dSOx9cWI79U46EzIyKShvkZERERBSo+B5EI3idERK7Dxh0iN9Lq9Cgor8PGkioUlNdBq9N7+pTcTqvTY2n+YZv7vLy1LCDThoh8iy/mZ4xDRCSVVqfHrmN1WFNYiV3HmG8QURdffA4i9+N9QkTkWpyWjcgFLM05vK2shsOQARRW1vfosWPuVGMbCivrkZ0S456TIiJygLfmZ9bmved0GEQkFfMNIrLGW5+DyLvwPiEici027hDJzFIhOCosGA2tnT32NQxDXpyXHjAFZI2dBzup+xEReYo35mfWKmIvH5aI93ZV9Ng/EOMQEYkxTKNjjvkGEQHe+RxE3of3CRGRa3FaNiIZWZtL1lLDTneBNAxZHREq635ERJ7ibfmZrfnMLTXsdBdIcYiI7NPq9Hhh0yGb+7yw6RDzDaIA5m3PQeSd4nqFyLofERGZYuMOkUxE5pK1xjAMORBkJkcj0c4DflKkCpnJ0W46IyIix3hTfuZMDAICKw4RkX0F5XWot9M5qb61EwXlde45ISLyOt70HETeS6sX6wQguh8REZli4w6RTETmkrUlUIYhBykVmJ2bZnOfWRNSEaRUuOmMiIgc4035mbMxCAicOERE9u2uqJN1PyLyP970HETeS7TzEDsZERE5ho07RDJxtlIskIar5w5WY3Feeo+eXkmRKs7fTkQ+xVvyMzkaZgIpDhGRbaIdqNnRmiiwectzEHkvxhMiItcK9vQJEPkLZyrFAnG4eu5gNcalxqOwsh6apnaoI0KRmRzNnl1E5HO8IT9ztmEmEOMQEVmXkxKDN3eWC+1HRIHNG56DyHsxnhARuRYbd4hkYphz2JFpcQJ1uHqQUoFsPsQRkR/wdH7mTAwCAjcOEZFlo1NiEBUWjAYb6+5EhwVjNJ/jiAiefw4i78V4QkTkWh6dlm3z5s0YOnSoyb+ZM2cCAIqLi3HDDTcgIyMD1113Hfbv32/y3vXr12PixInIyMjAjBkzcPr0aeM2vV6Pl156Ceeddx7GjBmDJUuWQKfTGbfX1tbioYceQlZWFnJzc7FmzRqTY9v7bCJLtpXVoLVTZ3Of6DDT9lQOVyeSD2MKBbIgpQKXD0u0uc+tOf04bQqRAMaTrjxl/qQhNveZN2kIG4WJiGxgPGE8ISJyNY827hw+fBgTJkzAjz/+aPz33HPPobm5Gffccw9ycnLwxRdfICsrC/feey+am5sBAEVFRZg/fz4efPBBfPLJJ2hoaMDcuXONx33rrbewfv16LF++HK+++irWrVuHt956y7h97ty5aGxsxCeffIL7778fCxYsQFFREQDY/WwiS/JLNXh8bbHV3ijRYcFYnJeOjfefjxXTRuG5K4dhxbRRWHPXGL+uUNPq9Cgor8PGkioUlNdBq+NEuuQ6jCnkrdyRF+aXavDergqr22/N6YeZ4wZh7d1jAyoOETmC8YSIfAXLW96N8YSIiFzNo9OylZWVYciQIUhISDB5/bPPPoNKpcKcOXOgUCgwf/58fP/999iwYQOmTp2K999/H1dccQWuueYaAMCSJUswYcIElJeXIyUlBe+++y5mzpyJnJwcAMCjjz6KV155BdOnT8exY8ewdetWbNmyBf369cOQIUNQWFiIDz/8EKNGjcLXX39t87OJzGl1eizNP2xzH1WwEuNS4wNquHp+qQZL8w+bTBGUGBGK2blprEgkl2BMIW/kjrxQJA5tOliNGRcPDKg4ROQoxhOxfOXlrWXG51sicj+Wt7wf4wnjCRGRq3l05E5ZWRnOPvvsHq/v3bsX2dnZUCi6MnaFQoHRo0ejsLDQuN0QxACgT58+6Nu3L/bu3YtTp07hxIkTOPfcc43bs7OzUVlZiaqqKuzduxd9+vRBv379TLbv2bNH6LOJzBVW1ttd46CqqR2FlfVuOiPPM4xkMk+XqqZ2PL62GPmlGg+dGfkzxhTyNu7KC0Xi0KnGtoCKQ0TOYDxhvkLk7Vje8g2MJ4wnRESu5rGRO3q9Hr/99ht+/PFHvPbaa9BqtZg8eTJmzpyJ6upqpKWlmewfHx+P0tJSAEBVVRUSExN7bD958iSqq6sBwGS7Wt3Va8Ww3dJ7T506BQB2P1sKhZ92OjBcl79en4juaaA5I7Z4teZMu1+lmbX7QLRnzvg03++Zw9+Ca9LAkWP5e0wJpHvMX35XrswLzdMoUOOQLf5yH7lKoKQP40lPomnCfMU1AuW35w6BnJZyPmMEcjpKwXhimUi6VDW1CR2rqqktIO7DQP/N8fpN/xtoeP2m/5WLxxp3jh8/jpaWFoSGhuJf//oXKioq8Nxzz6G1tdX4enehoaFob+8qZLS2tlrd3traavy7+zYAaG9vt3tse9uliI+PlPweX+Lv1yciPj4SqX3F7o3UvjFQq/0vzczvgx1lNUI9c440duD81HhXnprb8Lfg+TTw95ji6fT1BF+/ZnfkhYY0CvQ4ZIuv30euxvTpifGkC/MV1+JvTz6BmJaueMYIxHR0NX+PJ4DYfdOhqBY6VodCGVDxJNB/c7x+Xn8gi4uT9/o91riTnJyMnTt3Ijo6GgqFAsOHD4dOp8Njjz2GMWPG9Ags7e3tCAsLAwCoVCqL28PDw02CmkqlMv4/AISHh1t9r71jG7ZLUVPTCL0frmeoUHT9EP31+kR0T4NBkSFIjAi1+YCdFKnCoMgQaDSNbjxL17J2H5QdrxN6f9nxOgyODrW/oxfjb8E1aWA4phT+HlMC6R7zl9+VK/NC8zQK1Dhki7/cR64SKOnDeNKT6HfOfMU1AuW35w6BnJZyPmMEcjpKwXhimch9E6LXCR0rRK8LiHgS6L85Xj+vn9cfidOnG2Vt4PFY4w4AxMTEmPydmpqKtrY2JCQkQKMxnSNWo9EYh5YmJSVZ3J6QkICkpCQAXUNNDXOMGoatGrZbe6+tY5sPaxWh18Ovb1Z/vz4Rej2gVCgwOzcNj68ttrrfrAmpUCoUfple5veBurdYJaW6d6jfpAd/C96RBv4cU7whfd3N16/ZHXmhIY0CPQ7Z4uv3kasxfSxjPGG+4mr87cknENPSFc8YgZiO7uDP8QQQu28SI1RCx0qMUAXUPRjovzleP68/0K9fTkp5Dyfuhx9+wNixY9HS0mJ8raSkBDExMcbF3vR/XK1er8fu3buRkZEBAMjIyEBBQYHxfSdOnMCJEyeQkZGBpKQk9O3b12R7QUEB+vbti8TERGRmZqKyshInT5402Z6ZmWk8tq3PJrIkd7Aai/PSkRhh+qCdFKnC4rx05A5We+jM3C8zObpHOphLilQhMznaTWdEgYAxhbyNu/NCxiEieTCe/In5CpF3YnnLNzCedOH9SkTkWh5r3MnKyoJKpcKCBQtw5MgRbNu2DUuWLMFdd92FyZMno6GhAc8//zwOHz6M559/Hi0tLbjiiisAADfffDPWrFmD1atX48CBA5gzZw7Gjx+PlJQU4/aXXnoJO3fuxM6dO7F06VLcdtttAICUlBRcdNFFeOyxx3DgwAGsXr0a69evx1/+8hcAsPvZRNbkDlZj7d1jsWLaKDx35TCsmDYKa+4aE3AF3yBlV09PW2ZNSJW8gDiRLYwp5G08kRcyDhE5j/HEVPd85ZWbMpmvEHkBlrd8A+NJF96vRESupdDrPTcQqrS0FC+88AIKCwvRu3dv3HTTTZgxYwYUCgWKiorw1FNPoaysDEOHDsXTTz+N9PR043u/+OILvPrqq6ivr8eFF16IZ599FrGxsQAArVaLJUuW4IsvvkBQUBCuv/56zJ49GwpFV7CoqanB/PnzsX37diQkJOCRRx7BlClTjMe299miNBr/nENQoQDU6ki/vT4R3pgGWp0ehZX10DS1Qx0RiszkaJc+INlLg/xSDZbmHzaZqz0pUoVZE1L9pkLAG+8Dd3NFGhiOKZU/x5RAusf87XdlKS9MjAjFNaP6oH9MuEP5tb+lkSswjWwLlPRhPOnJ0e88UO4ZV/PldHR3WcMeX05LuchR3mI6imE8sUzKfZNfqsFLW0pRfabD+FpiRChm56b5Tf2AiED/zfH6ef28/q41h6Su42bzuJ5s3PF3/nqzBvqPERBPA3cVgqxVHrryQUkkDbytECg3/ha8q3HHnwXSPeaPv6vueWF5XQv+U3TCqfxaShr5ez5sjT/eR3IKlPRhPOnJke/ckI+0KZVQ6XQBk4+4gq/+9jxR1rDHV9NSbs7GeaajGMYTy5xt3EnoHYJHLx3Mxp0Awuvn9fP65W/cCZbtSERkwloh6JHxqYjtFSJbRVt+qcbiYrdVTe14fG2xR+dED1IqkJ0S45HPJiLyFoa8ML9Ug9e2H+2x3VX5ta3KuHGp8QHZ6ENE0nhjpT65lzeXNYjlLfIN1vKR6jMdzEeIiJzExh0iF7BVCJq7vsTkNWcKyFqdHkvzD9vc5+WtZRiXGs9KOyIiD3J3fm2vMi4qLBgNrZ3G11lZS0TmWKlPLGsQkbO0Oj2e33TI5j4vbDrEfISIyEFKT58Akb8RKQR1Zygg55dqJH9WYWW9SU9KS041tqGwsl7ysaXQ6vQoKK/DxpIqFJTXQasLwPGVRORz3Jl3uTO/FolD3Rt2AOdiERH5H61OjxcEKuP4zOffvKWsQf6D5cbAs7u8rsdzp7n61k7sLq9zzwkREfkZjtwhkplIIcgSR3q9aQQ/R3Q/R+Qf0uAlTtdBRD7G3VMNuTO/djQOAeyBTURdCsrrUC9QGVdQXocxA2LddFbkbt5Q1iD/wWkeA9Mvx+qE9zuX8YSISDKO3CGSmaOFG0d6vakjQmXdzxZLvaw27D+BOWuLe1Qisgc4EXkzw1RDonmXHL1M3ZlfO1PJxh7YRAQAuyvqZN2PfJM7YxfJw1tHxkh99iL/cbKxTdb9iIjIFEfuEMnMmcKNpQo5rU5vddHrzORoJEaE2uyhnRSpQmZytMPnBFjvZdVup7DAHuBE5G2krh8gtZeptTzbXfk14HwlG3tgE5FesD5YdD/yPVqdHlqdHlGqIDS0aa3uJ1fsIud568gYrt0U2BIFn0tF9yMiIlNs3CGSmUgFnjXmFXL2HtCDlArMzk2zuNitwawJqU49JNtaTNceQw/w7JQYhz+fiEhOUtYPqG/tlLSYuL0829X5tYEzcQhgD2wiAnJSYvDmznKh/cj/WIpn1sgVu8g5tspslp5Z3EnKsxfLjf4npleIrPsREZEpTstGJDNDg4tU5r3eRIeu5w5WY3Feeo+eLkmRKqcf4kV6WdnDHuBE5E1E86SqxjahXqaG6U5E8mxX5tfdORqHDOfCHthENDolBlFhtvsBRocFYzQrYv2OtXhmTu7YRY4THRnjqSnauHZTYIsNF2u0Ed2PiIhMceQOkQsYKvBEe7wBpr3epA5dzx2sxrjUeKvTtznKmUW5DdgDnIi8iWieVNvSIdzLNDM5WjjPdlV+bc5aHIoOC7a5SDp7YBMR0NVIPH/SEJujDedNGsL8ws+IlEGiw4KxaMpwjE6J4ffvJbx9ZAzXbgpstS0dsu5HRESm2LhD5CKWKvBqWzqwbGuZycN3UqQKsyakmvR6c+QBPUipkP1h3dneU+wBTkTeRnTtG9Heg5qmdsl5tivya0usNSRtK6vp0ehjKRYRUWAzNBK/tKUU1Wf+rHTzhjU8yDVE4ll9ayeUSgUbdryIt4+Mcee6g+R9GlqsdypyZD8iIjLFxh0iF7JUgTchTW23x7a3PKA723uKPcCJyNuIrlUWbWc6IgN1RKjX5NmWWIpD7ho9RES+r3t+0aZUQqXTMb/wY94cz8g6bx8Z4451Ysl7KQUXgxDdj4iITLFxh8jNRHpse8sDur1eVgoAUWHBCA1SmPToZA9wIvJm1qYs6553aXV64V6mhZX1Qp/rTdONuGv0EBH5viClAjn9Y6BWR0KjaYTeM8t2kBt4SxmEpPGFkTEiz17kn0b3i8EbKBfaj4iIpGPjDpEX8pYHdJFeVvMnDcEl7AFORD7G3ugVKb1MvSXPJiIicgbjmW/ylZExHDkcmLJTYuyu+RgdFsxOR0REDuLARyIvZHhAt8VdD+iGXlaJZj30kiJV+PdfRyN3iNrYA/zy4YnG9SSIiLydvbzLVv63OC/d2MvUm/JsIiIiRzGe+S7RZxZPY7kx8AQpFZg3aYjNfeZNGsJ7gYjIQRy5Q+SlvGnouqVeVln9opGUGAWNptFt50FE5G6ivUy9Kc8mIiJyFOOZ7+LIGPJWVvOVCBVm5TJfISJyBht3iLyYNz2gm6/PoGAZgYgChOj6NN6UZxMRETmK8cx3cU098lbd85U2pRIqnY75ChGRDNi4Q+Tl+IBOROQ7mGcTEZE/YDwjIrkFKRXI6R8DtToSGk0j9HpPnxERke/jmjtEREREREREREREREQ+hI07REREREREREREREREPoTTshF5Ka1Oz3muiYj8BPN0IiJyJcYZIvJ2hnyqraKBa+4QEcnEocadsrIyJCYmIjIyEj/88APy8/ORnp6OG264Qe7zIwpI+aUaLM0/jKqmduNriRGhmJ2bhtzBag+eGZG8jh79HfHxakRERGDnzh348cfvMXToUNxxx62ePjUi2TBPJ3IP85jy3/9+j9GjM1hGIb/HOEMkL8YT+TGfIiJyDcnTsn3yySfIy8tDSUkJiouLcf/996O8vByvvPIKXnnlFVecI1FAyS/V4PG1xSYPPQBQ1dSOx9cWI79U46EzI5LXmjVf4LbbbkRp6UEcOnQATzwxC8ePV2LVqn8znpDfYJ5O5B7WYgrLKOTvGGeI5MV4Ij/mU0REriO5cef111/H4sWLMWbMGHz++ecYPnw4Xn/9dSxbtgyrV692xTkSBQytTo+l+Ydt7vPy1jJodXqXfHZBeR02llShoLzOJZ9B1N2HH76LBQueRlZWNr76ai3S0oZg6dJX8cwzixhPyC94Mk8nCjTWYgrLKOTPGGesY9mGHMV4Ii/mU0REriV5WrZTp04hOzsbALB161bceOONAICzzjoLZ86ckffsiAJMYWV9j94s5k41tqGwsh7ZKTGyfS6HSJMnVFdXY9SoTADAf//7A66+eioAICEhkfGE/IKn8nSiQGQtprCMQv6MccYylm3IGYwn8mI+RUTkWpIbdwYNGoR169YhLi4Ox48fx8SJE9HR0YE333wTw4YNc8U5EgUMjZ2HHqn7iTAMkTZnGCK9OC+dhSByiQEDBmDTpg2IjY3FqVMncfHF49HZ2YmPP/6A8YT8gmheve1wDQuzRE6yFlNYRiF/5omyg7dj2YacxXgiL+ZTRESuJblx5/HHH8fDDz+M+vp63HLLLUhNTcUzzzyDzZs3Y8WKFa44R6KAoY4IlXU/e0SHSI9LjUeQUiHLZxIZPPjgI3jyySfQ0NCAa6+9HmefPRAvv7wY27ZtxcqVr3n69IicJppXbyipwt/HDWI+S+QEazHlhx++YxmF/Ja7yw7ejmUbkgPjibzieoXIuh8REZmSvObO+eefjx07dmDnzp148sknAQAPPPAAtm7dipEjRzp8Ivfccw+eeOIJ49/FxcW44YYbkJGRgeuuuw779+832X/9+vWYOHEiMjIyMGPGDJw+fdq4Ta/X46WXXsJ5552HMWPGYMmSJdDpdMbttbW1eOihh5CVlYXc3FysWbPG5Nj2PpvIVTKTo5Fop/CVFKlCZnK0LJ8nZYg0kdyys8/FunWb8dVXWzBr1uMAgNtvvwtffLGe8YT8QmZyNGLC7PejqW3pYD5L5CRLMeWOO+5iGYX8mrvLDt6OZRuSA+OJvERX0uGKO0REjhFq3Pnll1/Q2dlp/P+CggIcOnQIv/zyC3755Rf89ttvKCwsxC+//OLQSXz11VfYtm2b8e/m5mbcc889yMnJwRdffIGsrCzce++9aG5uBgAUFRVh/vz5ePDBB/HJJ5+goaEBc+fONb7/rbfewvr167F8+XK8+uqrWLduHd566y3j9rlz56KxsRGffPIJ7r//fixYsABFRUVCn03kLFuLewYpFZidm2bz/bMmpMrW04xDpMndCgt3G+NJYeFuFBUV4siRwygs3I3Cwt04duwo9u8vYjwhvxCkVOCK9CShfd2dz3KhafIHIjGFZRTnaXV67DpWhzWFldh1jPmFN3F32cHbsWxDjmI8cV08qW3ukHU/IiIyJTQt26233or//ve/iI+Px6233mp1P4VCgZKSEkknUFdXhyVLluCcc84xvvb1119DpVJhzpw5UCgUmD9/Pr7//nts2LABU6dOxfvvv48rrrgC11xzDQBgyZIlmDBhAsrLy5GSkoJ3330XM2fORE5ODgDg0UcfxSuvvILp06fj2LFj2Lp1K7Zs2YJ+/fphyJAhKCwsxIcffohRo0bZ/Wzyf1qdHoWV9dA0tUMdEYrM5GjZCkQii3uOS43HvRcMwEe7K9HQ2mncLylShVkTUmWdI5pTOZC7PfTQvVi7diNiY+Pw0EP3Wt2P8YT8xbi0eHy0u9LufrG9QlBQXueS2GNOdKFpV8ZDIjkwprg+puSXavBS/mFUd8svEiJC8SgXpvcauYPVWJyX3iNfd0XZwduxbEOOYjxxXTzh75KIyLWEGncOHDhg8f/lsHjxYlx99dWoqqoyvrZ3715kZ2dDoeiqQFAoFBg9ejQKCwsxdepU7N27F3fffbdx/z59+qBv377Yu3cvQkNDceLECZx77rnG7dnZ2aisrERVVRX27t2LPn36oF+/fibbX3vtNaHPJv8mWuHl6LHtLe4JoMfnR6mCcFN2P9w5tj+ClApZK9sMUznYmr4gkKZyINf74YdfLP5/dwoFoFZHSj424wl5gr08WSSfjQ4LxsJvDqD6zJ89FuWKPeZEF5p2ZTwkkou9mOJoPAEYUwDr+UU1F6b3OrmD1RiXGu+1DfLu6izAsg05ivHEdfEkMzka0WHBqO/WcdVcdFgwf5dERA4Satwxp9Vq8cMPP+D333/H1KlT8dtvv2HQoEGIjJQW7Hbs2IFdu3Zh3bp1WLhwofH16upqpKWZDi+Pj49HaWkpAKCqqgqJiYk9tp88eRLV1dUAYLJdre4qdBi2W3rvqVOnhD5bCoV3PEvLznBd/nZ9+YdsV3gtyUtH7pCue0lqGogs7vnCpkMWH3ga2rRYuf0o0tS9AQAvWahsezQ3zXhuUgQHKfBobhrmWLhug9kTUhEc1PNC/fU+kIJp4HwaaLVa7Ny5A+Xlx3DllVfh2LGjOPvssyUXnhhP/Icv/a7yD2ns5ski+aylvN9S7DFwNI1EF5rW6/V4Yl3PXqm2zsnb+NJ95An+mj7mMaW8/CiyskayjNKNlGfXp785aHOfp785iPFpXJheClf+9oKDFMjpHyP/gZ0kEisdYSktnSnbBCp/jQfOYjwRI3LfKBRAS4fO5j4tHTooFIFxHwb6b47Xb/rfQMPrN/2vXCQ37pw4cQJ33nkn6uvrUV9fj0svvRSvv/469uzZg9dffx3Dhg0TOk5bWxueeuopPPnkkwgLCzPZ1tLSgtBQ0yGZoaGhaG/veiBsbW21ur21tdX4d/dtANDe3m732Pa2SxEf71jPDl/hT9en1emxbNvPVrcrACzbdgTXnXe2SQFWNA12lNXYXdzTVk8WBYAXvi1FfXNHj4UGq5raMWdtMf7vltG4clQfofPpbpo6ElFRYXh6XTFO1LcaX+8THYanrkrH5JG2j+lP94GjmAaOpYF5PMnLuxKfffYh44kFgXiPyXHNWp0eP/92GlWNrUiMDMOYgXGyVUJu2H8Cj68t7pEnG3q0//uvo435p618tqVDizorc4xbiz0GUtNIJBadamzDEhsNQPbOydsE4m9HCn9KH0sxZfXqDzFvHmNKd6Lf+Q+HqtHcobW5T3OHFofq2nDxkARJ50D+9duzRUqsdJR5WjpbtpGDK58/XCVQ7kkRjCfiRO6bHw5Vo11ru3GnXasLuHgS6L85Xj+vP5DFxcl7/ZIbd5555hnk5ORg4cKFxvk9X375ZcyfPx/PP/883nvvPaHjLF++HCNHjsTFF1/cY5tKpeoRWNrb240B0dr28PBwk6CmUqmM/w8A4eHhDh/bPBiLqKlphN4P1xtVKLp+iP50fbuO1Zk8/JvTAzhR34rNhRXI6R/TIw20Oj32VNRDc6Yd6t6hyOpnOtVA2fE6p85PD1it/DN48KPdeKFxOCYOlf5AlHNWBL6cfq7Fa9BoGi2+xx/vA6mYBs6lwYIFT2LkyAw8+ugTuPzyCTh9ugnz5z+DRYueYTwxE0j3mFy/K1f1FNbq9Cg4Vocn1pf0qKwCYHztqTW/IiuxtzEWWMpndTo9Hvhsn9XPMo89Bo6mkWgsOn3Geryxdk7ehvmzbf6YPpZiyoIFz2Dp0kWMKd2Ifucf7vhd6Hgf7vgdw+Okx7VApVAAMbER+HZvBaqbLJcb/IVWp8eTX+6XFCulsJWPOVK2kYurnj9cxR/jgbMYT8SJ3DcfbP9N6FgfbP8tIOJJoP/meP28fl5/JE6fbpS1gUdy486uXbvw6aefIigoyPhaSEgIHnjgAVx77bXCx/nqq6+g0WiQlZUF4M9gtHHjRkyZMgUajcZkf41GYxxampSUZHF7QkICkpKSAHQNNTXMMWoYtmrYbu29to5tPqxVhF4Pv75Z/en6NHZ6Mnffr/s16/XAlkP21yVQ93b94oA6PfDEuhIsVigcmv9cqVAgOyXG5DWR79ef7gNHMQ0cS4PCwj1YufJtKJVBxmMEBQXj9tvvwp13/lX4OIwn/smZa7a1rswcJ9aJsLQOjTWnGtuwp6LeJF81z2c3llT1fKMF5rHHQGoayRmLrJ2TtwnE344U/pQ+1mIKyyimRL/z5nbbo3a67+cv95A75B/SYNm2n006lfnremZ7KuqFRouax0qprN3TjpZtnOGq5w938Kd44CzGE3Ei982JhjahY51oaAuoezDQf3O8fl5/oF+/nJRS3xAWFoaampoer//222+IiIgQPs57772HdevW4csvv8SXX36J3Nxc5Obm4ssvv0RGRgb27NkD/R9Xq9frsXv3bmRkZAAAMjIyUFBQYDzWiRMncOLECWRkZCApKQl9+/Y12V5QUIC+ffsiMTERmZmZqKysxMmTJ022Z2ZmGo9t67PJP6kjxCq8zPczrNNjXnAxrEuQX9r10GRY3NMdXt5aBq0ugHNJ8hlhYWGorT3d4/Vjx44ynpDDRNeVkZpPGipsRBp2DOx1HHA09jhKJBbFhocIHUuucyKSi7WYwjKKYzL7Rcm6H3XFkTlri3vMFmBebvAXUjrP+QNXPX+Q+zGeyOusKLFnRtH9iIjIlOTGnZtuuglPPvkkvvvuOwBdAe7zzz/HP/7xD1x//fXCx0lOTsaAAQOM/3r37o3evXtjwIABmDx5MhoaGvD888/j8OHDeP7559HS0oIrrrgCAHDzzTdjzZo1WL16NQ4cOIA5c+Zg/PjxSElJMW5/6aWXsHPnTuzcuRNLly7FbbfdBgBISUnBRRddhMceewwHDhzA6tWrsX79evzlL38BALufTf5JpMIrKVKFzORo499anR4vCT7ABykVmJ2bZnPfqDDJA+ksOtXYhsLKelmOReRK11xzHV588QVs3/4jAD3Ky4/hq6/WYvHi5xhPyGGFlWI9haXkkyIVNpbYawBxJPY4QyQWzbk0za3nRCQXazGFZRTHTMtMhr2JshR/7Ef2BWLFv7s7MHiaK54/yDMYT+Q1WC3WICa6HxERmZJcmzxjxgxERUVh4cKFaGlpwT333IP4+HjcfvvtmD59uiwnFRERgddeew1PPfUUPv30UwwdOhQrV65Er169AABZWVl45pln8Oqrr6K+vh4XXnghnn32WeP7p0+fjpqaGjz44IMICgrC9ddfj9tvv924fcmSJZg/fz6mTZuGhIQEvPDCCxg1apTQZ5P/0Or0KKysh6apHeqIUDwyIRVz15VY3X/WhFST+aB//u208AN8dkoMcgersTgvvceUPkmRKsyakAoAFofxG0SHBaO+tVPo2vylBxz5t9tvvwsRERF46aVFaG1txWOP/R2xsXG46aZb8NBDD8jyGYwngccVPYVFKmzMWWsAcTb2OMteLModrIZSqbAZj+Q+JyI5WIspd955B8soDggNVuKvOf3w3q4Kq/v8NacfQoMl9xUMSFIq/p2ZosybGDow2Lpuf+osEGgjlfwZ44m8znSI1WGI7kdERKYUer20md7Wr1+Piy66CDExMWhuboZWq0VkpHyLAPkTjcY/F4hSKAC1OtKnr8/SugmJEaG4fFgiNh6oslrhZaBQAP+taMDfPy60+1nPXTkMlw//c/5a84q9zOQ/F1G1dF6Gz9fp9Ji73noFYHcrpo1CdkqMzc9ylj/cB85iGjiXBps3b8DYsecjKioaLS0t0Gq1iIiIMB6T/hRI95izv6uC8jrc92mR3f0M+aSIjSVVWPD1AUnncfPoZIxLi7ebx0uJPQZy5D324oOteOSt6wV0x/zZNn9MH0sxJTIygvHEjNTv/NEvf8W2sp5Tco9LjcdL14yQ8cz8m2gcMS83eBNHyhXW1qAxcGYNGm/Lx1zx/GHAMp17MZ6IE7lv/v3jb3hzZ7ndY905NgX3XzRQpjPzXoH+m+P18/p5/ZGoqWlEfLx8MUXyyJ2nn34an3zyCWJiYtj7mHySrYUu39tVgUVThiO2V4jdh+fEyDChzzOfaiBI2XNxT4PcwWqMS43v8fC+rawGy74rE/o8Qw84a5WI/rhgK/mmpUsXY+XKtxAVFY3w8HBPnw75CZGewtFhwZJ6CkuZMkapAHR64KPdlfhod6Ux3wUsj86UGnvkYisWAdbjEUfskLdiTJFffqnGYsMOAGwrq0F+qYbPlIJ8fYoyR8sVIqNF/YWrRiqxTOd+jCfyykmJEWrcyfGTUYtERO4meRz92LFjsX79erS3czgx+R6R+a7/te0IMpOjcfnwRGSnxFityBozMM4l6xIYKtwMn7+trEbSIt6zJqRafY/UBVu1Oj0KyuuwsaQKBeV1fjUPOHne6NE52Lx5I+MJyUpkXZn61k6rFZaWiKyNEx7S9Uhlnk0a8t3nNx2y+X7R2ONO5vHIG87JgPGJzDGmyCsQ14hxJXevsSYnQ8c4R8sVuYPVWHv3WKyYNgrPXTkMK6aNwpq7xvhdw4TI84fUaU2dTXtyDOOJvDIE8zXR/YiIyJTkkTs1NTX4v//7P6xYsQJxcXFQqVQm27ds2SLbyRHJTc75roOUCjyam4Y5LlyXQMoi3oYecONS45G3aqfNfV/eWoZxqfE2z429xMjVamtP4+23X8e7776JmJhYhIZ2xROFAlAqFYwn5LBxqfF21ykTyQcNDBU2tqaWCQ1SoqVDZ3V7g5010/xtrQVXYnwiSyzFFEM8AVhGkSoQ14hxpe5xRAHAUpOYN65nJtrIZy+e2hst6i/kHKkkV9qTdIwn8tpdUSe833lnx7n2ZIiI/JDkxp1p06Zh2rRprjgXIpeTe6HL3CGunWpAdBHv6zP6YFTfKESHBaOgvM7pwritqeseX1uMxXnpuHQIK9DIOXl51yIv71qL2yIFpz0ksqSwst5mww7QlQ8WlNdhzIBYoWPaqrC5+pyzsHL7UafOGeAiyyJE4hMbeAKTtZjCeOIYLg4vv9zBaizJS8eybUdwor7V+Lo3T1HGRj5xhnVxOjp1WDh5KPQAaps7HJ7WlGnvOYwn8vqm+JTwfmzcISKSTnLjzrXXdgW5pqYm/P7771AqlRg4cCDnIiWfIDqPdVyvEBSU1wmtM+DKdQlEC8yf7T2Bz/aeAABEqYKcOrZoL7HxafFCn0NkzRVXTAEANDefwbFjx6BUKtC//9kIDw/jgqXkFNG8c+66Ysy/fKhwhZq1/P7bg9XOnK6ROiLUpYsm+zopvZiDg5hmgcZSTBkw4Gz065fg4TPzTbG9QmTdj7rkDlHjuvPOxubCCp/I59nIJ8bWiFJHG16Y9p7DeCKvM+1aWfcjIiJTkht3Wlpa8OSTT+Kbb75BZ2dXr9jQ0FBce+21WLBgAUJC+IBP3iszORpRYcE2p8fpFaLEwg0HJU334qqpBhxZVLWhTeyhyNqxRXuJ7amox+TEKMnnR2TQ2tqKF198Hlu2bIZW23XfhoSE4sorp+C5555mPCGHieadDW1ayaM9LOX3ciyAHR0WjNrmDuSt2snpxqyQ0os5p3+Me06KvIa1mDJ1KssojhBtavDOJgnvFqRUIKd/DPQ+sFyRaHyTIw76KleNKGXaew7jibx4LxMRuZZS6hv+8Y9/4MCBA3jjjTdQUFCAX375BStWrMCuXbuwaNEiV5wjkVPMF122V5Jq7tC5ZNFKRxZ/Fll81RG2FmwV7iV2Rr5eYlwYOzAtWfI8Dh8uxcsvL8fGjdvwzTdbsXjxyygs3MN4Qk6Rmnc6uyi4yOfZqwDt0Ooxd32JyxdN9uX8lr2YyRZLMWXJkpdZRnGQ6HOenM+D5H1E4putcoW/Ex1R6kis9Ze098XnDsYTeQ1PipB1PyIiMiV55E5+fj7ee+89jBgxwvjaBRdcgBdeeAF33303nnzySVlPkMgZlobIO+OFTYccmu7FkcWfDVPzXDokAR/trnTqvM3ZWrBVuGdNb3kanbgwduD68cfv8f/+32sYOnSY8bVzzx2LefOexGOP/Z3xhBzWfeFqEaca27C7vA5KpcKhaXKClApcPiwR7+2qsLqPvaqM5g7boy4N8ceZqXt8Pb9lz0+yxVpMYRnFMacFG21E9yPfJBJPbZUr5GQ+bWlWP883arhyXRxvSntH+epzB+OJvEpONQnvd/U5Lj4ZIiI/JLlxJz4+HjU1NT1eb29vR0QEW9rJe1gbIu+M+tZOvLXzGO6+YIDT52HojX3z6GSMS4s3qUi09CCsVABSOzqZT0HXfcFWa+s6GHqJ2SqoJEWqZClQcWHswBYbG4va2tM9Xu/oYDwh5+UOVmNxXjqe33TI5lScBk+sLzHZz1D5ILKmWn6pxmbDjhwM8eeu88XjT3f+kN+Kxidv78VMrmEtprCM4ph6gXxTyn7kuwzx1Lxs0r1c4Qgpa8xZayR45pqRyDnL9u/blWvZiY4UrWpsE17PtTtXpb07+PJzB+OJvDjymojItSQ37tx7772YP38+7r33XmRlZSE4OBglJSV49dVXce211+KXX34x7nvuuefKerJEokSGyDvq492VuPO8/rKdx0e7K/HR7kpjRSIAiw/Choadm0cn46woFZZ9d8Tu5/9zynCLPdHt9aKy10ts0tAEpwtFUhbG9uYeaeS4W2+9A//857O49dbbMXJkBoKDg1FaehBvvPEarrtuKuMJOS13sBqRoUF44LN9dvc1bwAyVD5EhwWbVF6a9zh1Zbwx9/HuStwxtr/k0aP+kt/6Qy9mch1LMeXw4YN4882VLKM4oFOnk3U/8m25g9VCnR1ESRnRYauR4P73d2NxXjomWGkkcPXIEdGRoi9/dwR1LR0OnYPcae8Ovv7cwXgir1DBxSBE9yMiIlMKvV7aUo7Dhg2zvxMAhUKBkpISh07KX2g0jT6xUKZUCgWgVkd69fUVlNfhvk+LXHb8FdNGYfLoFLtp4Mh5mI+2MZcUqcIXd56La9/42W7v5TV3jbHYw9xWxZihF9Wr247Y7Im+JC8d0y4Y6PB9IJo2K6aNkjyNgbv4wm/B1ZxJg4svFisMMZ74bzyxRO7flVanR96qnbJNz2lgyCtdHW/MrZg2Cjn9YySlkT/kt91Zqqwz78XM/Nk2f0wfxhQxot/57C/34fuyWrv7XZIai6XXcB4dUf7425NKtCwC2I/hCgCJTpZ5pDAfBXROnyi7ZTJbvGH0iivuSV9/7mA8ESdy39zxQQH2nzxj91gjz+qNt/6SLdOZea9AjwO8fl4/rz8SNTWNiI+PlO24kkfuHDhwQLYPJ3IVVw/pFV5k1oHzsDd90KnGNuw70YBHJqRi7jrrD5OWRteI9qK6aGAcNh6osrnf0q1luO68s23uYwuHZ9MPP/xi8XVDwCNyRvcKmGtG9cHK7UdlPb6hx6m78yhHPs/f8ltf7MVMrmcppjCeOK61XazELbofESB9RIe9NW30sLymjStGjlgbBWRvzT05z8FX+PpzB+OJvKoFv2fR/YiIyJTkxh0AKCsrQ2JiIiIjI/HDDz8gPz8f6enpuOGGG+Q+PyKHuHoxZXVvzy7qvO1wDbYcqra5z3u7KjCyb5RJbzDRRT8/23tcaL+ffzuNwdGOXSMXxiYAOHr0d8THqxEREYGdO3fgxx+/x9ChQ3HHHbd6+tTIh1mqgOkdGoQz7VrZPsNQmSQ1j4oJC0adE2tUOJIn+mN+G6RUeGVvX/Is85jy3/9+j9GjM1hGcUCY4Pw4ovsRAeJlEUNjjaONBFI/xx5bU8O9t6sCt+b0w8YDVSafGRsegtpuU7E5ew6+xB+eOxhP5NPUJvb8LbofERGZkvw0/sknnyAvLw8lJSUoLi7G/fffj/Lycrzyyit45ZVXXHGOREK0Oj0KyuuwsaQKOp0eiS56WEyKVCGrn9hizYbFn+X20e5KoeH/L28tg1b3Z49K0QJSRV2r0H5VjWL7WSKSNlwY27+tWfMFbrvtRpSWHsShQwfwxBOzcPx4JVat+jfjCTnMUAFjnkfK2bBj8MuxWlQ1tiEmPERo/94hQZgyMhEhDtaFOponMr+lQGAtprCM4phLUuNk3Y8IkD6iw9FGAjlHjoiMAtp0sBr/mT4GK6aNwnNXDsOKaaMwaViCbOfga3z9uYPxRF4RoWIj00T3IyIiU5KrF15//XUsXrwYY8aMweeff47hw4fj9ddfx7Jly7B69WpXnCORUfcGnILyOmPDRX6pBnmrduK+T4uw4OsDeOCzfWhqc7xntC1SFms2LP4sJymPPIbeYAaiBaR+MWFC+yVGiu1niUjacGFs//bhh+9iwYKnkZWVja++Wou0tCFYuvRVPPPMIsYTcohIBYyc3vipHE9+c9BkkWRbznRo8f6u4+hwcP1xR/NE5rcUCKzFFJZRHHOmXSyjEt2P/Iu1Mpk9Uhtr7DUSKGC5kUDOkSOio4D2nWhAdkoMLh+eiMzkaGwssT3FtdRz9SW+/tzBeCKvXqFinaBE9yMiIlOSp2U7deoUsrO7FjnbunUrbrzxRgDAWWedhTNn7C+SRuQoqfMcNztae2aF+WLNonIHq7E4L73HuVsTHRaMehtT9kid2bx7bzBDAcnWeSRFqnB9Rl98sKvC7n5jBsah9nSTxDP6k7W0cTStybdUV1dj1KhMAMB///sDrr56KgAgISGR8YQcIlIB44vkyBOZ35K/sxZTWEZxTKzgiETR/ch/WCuTzc5NsxtLRMsihsYaQyOBpSnRDGZbaCSQ+jm2ODIKqLCyXmgK1tjwEK8dveIsX37uYDyRV3JMGH6rtT/jR7JgB1MiIjIluXFn0KBBWLduHeLi4nD8+HFMnDgRHR0dePPNNzFs2DBXnCOR3XmOXWXKiCScNyDWocWauy/mrY4IxX+mj8G+Ew3YdrgGH+2utPq+JyYOhlKpEG4Msqd7bzCRAtKsCakIDVY6VJByBBfGDlwDBgzApk0bEBsbi1OnTuLii8ejs7MTH3/8AeMJCTHPZ6sa2zx9SrK6eXQyxqXFO5wnmqfPuNR45rfkt6zFFJZRHBMZFiTrfuR55jHBkfzfVpns8bXFWJyXbrPSXrQs0v28bDUSPH31COScFQG9We83Rz7HGkdGAYk2CE0enujXMdhXy3mMJ/IKF5yPWHQ/IiIyJblx5/HHH8fDDz+M+vp63HLLLUhNTcUzzzyDzZs3Y8WKFa44Rwpw7p5mxyA6LBgLJg0xefg0ForOtCO1bzsGRYZAqej5cGqrR9usCanI7BdttfFm2XdlmJ2bhrV3j8WbO4/ho4IKNDq4uKClHmmivajs7jfEcsHNkYIjF8YOTA8++AiefPIJNDQ04Nprr8fZZw/Eyy8vxrZtW7Fy5WuePj3ycpby2ZgwsccaBWyPgrS33dUUAF64ajgmDjGdr180BgHO9awm8kXWYsoPP3zHMooDPttzQni/iwYxT/F2csQEkTLZy1vLMC413uazvyMjOiw1EmT1i0ZSYhQ0mkbZPscSR0YBiTYIRZo9t8jRAOdtfLGcx3gir8p6sc5XovsREZEphV5v3s+lp1dffRV33HEHIiMjcfz4cZx11llobGxEdHTXA4xGo0F0dDRCQjgsvzuNprFHLyJ/oFAAanWk266voLwO931a5PoPMmPe80y0UGStR5v5cb89VI2560qs7nfZEDU2H9LIeg3diRYerO1n6T4ItMpEd/8WvJHUNHjjjddw441/QUREBE6ePInExEQ0NTUhKioKAHD6dA2io6Nx1lmxLj5z3xJI95jIPWUvn7UlKVKFmZcMxPyvDjhxlq5193n9Mf38ASZ5spT8VTQO+TPmz7b5S/rYiym1tTUYODCZZZRuRL/zy/+9Haeb7U8rFdcrGBvvv0CGMwsMht/eqaoG7KlwTyW+XDFBtEy2Ytooocp8ZxsyRPMxV45YMjBPQ61Oj7xVO4VmYTC811PlKH+JB85iPHGMyH2Tu/xHNLbZnzI/UqVE/oMXyXRm3ivQf3O8fl4/rz8SNTWNiI+PlO24QuMe33jjDdTXdy3Kfumll6Kurs7YsAMAarWaQY5cRnRYu5zuPq+/xQYb8wd0wxQE+aVdjTDtnTos2lxq89gvby1De6cOL9vp+eZMw05SpEpoWgTDop/ZKTFWCzmi+4mmEQW2Dz98F42NDQCAadPyUF9fbyw0AUBcXDyCgyUPKqUA4uxozlkTUjFpWCIW56X3WKQ5KVKFm0cnO3uKTlv10zHkrdppzDel5K+iPasNi187uig2kTcQiSksozhIJ7h2peh+ZLRh/wlctXIn7vu0CAu+PoD7Pi0yyfMdYS0vlxoTbHFk7RlbRMsYzpLjcwyjgCw9N1gqcxmmhRPx8tYyfHuwmuUoD2M8cZ1OrVicEN2PiIhMCdWgnX322XjooYcwbNgw6PV6PPfcc1CpVBb3XbRokawnSCQ6rF1On+6pxKCE3pg4JEG4UKTT67F4c6ndxTNPNbbh0TW/ovpMh5ynjAhVEK4acZZT6zM4Sq5pGsj/paQMwPz5jyEtbQj0ej3+9a8Xe8QThQJQqUIYT8iiwsp6oZ6wMeEhqGv5M5+1NPWkpXng39x5zGXnLoWhQmfRlOFY9l2ZzX27568i6XOqsQ27y+tQeLwBHxdUoKHb1J/+PNqS/I+9mGKIJwDLKFLFR4TidKv9BbDjPfCc7svyD3U11ps3pYiuWWPxmDZGfESHBQvFhMLKerujbRxZe8afSF0/JnewGvdeMACvbT9q87inGtuweAvLUZ7GeOI6QQqxCY+DrEw1TEREtgk17vy///f/8P7776OxsWs+W4GZ3IhkIzLPsdzq27SYu64ExTmNuHBQnFChyNYUa+Z2/F7r7CmaiA0Pwfp7xiI02DOLEIpWJooUHMm/Pf/8Enz++Sdoamr645We8YQhhmwR7RE8a/wgJEaqbFbAmM8Dn1+qwUo7lTDutmTLYdS22O4M0D1/FU2f2Wt+RUtHzx6SzlQwErmbvZjCeOK4sBCxUbSi+1FXZ6iX8g/brOKUWolvbbowQ14uOhpVJHY4svaMv5G6fkxKTLjQfnUS4jy5BuOJK4muZsnGHSIiRwg9jffv3x/z5s0z/j1//nxERES47KSIujMMa3d0fQVnvLerAu0+MDz4icsGe6xhB5B/mgbyX8nJ/TBz5mzj3w8//Ch69eptso9hHlIiS0R7BCdGqiRVgjg73Zur2GvYMTDkr6LpY6lhpzv2EiZfYC+mMJ44Lljwty+6H8nfGUokbm0oqRI6N5HYIVImmzUhlXGjGzlHMbEc5VqMJ64k2jLGFjQiIkdI7mo1depUlJRYH6Fw7rnnOnVCRJYY5jl+aUup7NOZ2fPVr6fc+nlSJEWoMCs31eO9qwN9mgZyzJVXXoVDhw72eF2hAKKjezGekEWZydFI6B1iMxY40nNYdLo3b2XIX+Ua7cpewuRrLMUUQzwBWEaR6mR9i6z7kfydoUTiVm1LB2LCgm1OGy0lZhrKZObTwJlPfeoqWp3eZFq0y+K8u8OpSEyODQ8R6sjBcpT7MJ7Iq0Mr1mgjuh8REZmS3Lhz6623Wnw9NDQUCQkJ2LJli9MnRWRJ7mA1IkKDMOOzfU4fKzY8BMMSe2PH0Tq7+za1a9ErNAjN7Vq7+7rTPRcMwJ1j+3tF7zhO00COeOihey2+HhISisRExhOybFtZDdrtFP4c6TnszT1ie4Uo0WxjpE33/FXO0a7enCZE5qzFFJZRHHOqyfYaklL3I/k7Q4nm0VekJ+Gj3ZVWt0uNmVLXnpGLpbWF+mw8hEfGDcIEN3R0M29YErlmkZg8Z2Ialm0tYznKizCeyKtNcCIU0f2IiMiU5MadAwcOmPyt1Wpx7NgxPPvss7jqqqtkOzEiS2rOOFfRFN8rBFqdHrUtHUINOwbe1LDjjsWupRZeOE0DOeKHH34x+Vur1aKysgLLli3Bdddd66GzIk8y5D1tFQ1Q6XQ98h5rawsYRIcFY96kIQ7lj67qETs0oTf6x/XC5oPVDh/DVsMO0DN/tdazOiosGA02em+bYy9h8iWWYsrx4xVYvvxlllEcIFrHxro4cYbOUNVN7VYnH5JSiS+aR49Li0dmv2hZR9tIXXvGWdbi/8n6VsyRaZ04W+UfSw1Llspklo4hMtpJqVCwHOVFGE+IiMiXOL1IR1BQEAYOHIgnnngCr7zyiqT3Hj16FNOnT0dWVhbGjx+P119/3bitvLwct99+OzIzM3HllVfixx9/NHnv9u3bMWXKFGRkZOC2225DeXm5yfa3334bF198MbKysjBv3jy0tPw5ZUBbWxvmzZuHnJwcXHTRRXjzzTdN3mvvs8lzRNcesKamucPmtARSJUWqsGjKcCT0DpHtmLbce8EArL17rEsbdvJLNchbtRP3fVqEBV8fwH2fFiFv1U7kl2psvs9QcEk0K2gmRaq4MDcJCQoKQv/+AzBz5iOS4wnAmOLruuc9f/+4EPd9WoRJ/96BpzccxDfFp/DL0Vq8sOmQ3eOMS4136PMNlW5yO1h9xqmGHVts5a+5g9VYe/dYrJg2Cs9dOQwrpo3CoinDJR2bvYTJlxliCssojgkWrEcW3Y+6GkQezU2zuY+USnyRuGXIyy3FhDV3jekRP7Q6PQrK67CxpAoF5XXQ6jw/TZKttYUMZ/fy1jKnztVW+cfQsGQ+sqaqqR2Pry3GMxsOor1TZ/MY9tKf5SjvxnjiHMYTIiLXkm0F9pqaGjQ0NAjvr9PpcM899yA2Nhb/+c9/8PTTT+Pf//431q1bB71ejxkzZkCtVuPzzz/H1VdfjQcffBDHjx8HABw/fhwzZszA1KlT8dlnnyEuLg4PPPAA9PquB7qNGzdi+fLleOaZZ/DOO+9g7969ePHFF42fvWTJEuzfvx/vvPMOnnrqKSxfvhwbNmwAALufTZ4VG+6eRhR7osKC8cFdY7H27jGYODQB12b0dennGR7s7zp/gEt7bdkrvIg08IgUHIlsqa2tlRRPAMYUX2ct72lo7cT6X0/hyW8O4oHP9qHeTuN8fWsnCsrrHDoHwwhEX9A9BtnKXw09qy8fnojslBhkp8QIN2CxlzD5C5ZRHDMiMUzW/ahL7hA1/v3X0bJU4ovEre55uXlMMM/jHe3g5WoiawsZ1olzhL3yz/N2Opas+/UULnrlR7tlKHvpz3KU92M8cUxKlNiEQaL7ERGRKcm559y5c3u8dubMGWzfvh2TJ08WPo5Go8Hw4cOxcOFCRERE4Oyzz8b555+PgoICqNVqlJeX4+OPP0avXr2QmpqKHTt24PPPP8dDDz2E1atXY+TIkbjzzjsBAIsWLcKFF16In3/+GWPHjsW7776Lv/3tb5gwYQIA4Omnn8b06dPx2GOPQa/XY/Xq1Vi1ahVGjBiBESNGoLS0FB988AEmT56Mn376yeZnk2clRqo8fQoAuiocd5TVoDGhFzKTo9E/Jtxln/XI+EG4MSsZAFBQXueyua1t9YozeHlrGcalxtudoo0LcJOIF154usdrzc3N2LVrp6R4AjCm+DKRvEeKXcfqEKRUQNPUjrheIdADqG3uQGyvECgAnG7usJqH5g5W49acfnhvV4Vs5+MKDa2dUCoUCFIqoJfQUVlkCk1nprYj8iRLMaWlpRm7dv3MMooDtAiSdT/60+SRfZCV2Bt7Kpxfs0Zkyi/A/pTL1qY9MzROuHraM1tE1xbqvp/oZ4k8g4hMZ2ovFIuUoQCWo7wF44m86gUX0xHdj4iITMnSNB4TE4PHH38cV199tfB7EhMT8a9//QtAV8+B3bt345dffsFTTz2FvXv3Ij09Hb169TLun52djcLCQgDA3r17kZOTY9wWHh6OESNGoLCwEDk5Odi3bx8efPBB4/bMzEx0dHTgwIED0Ov16OzsRFZWlsmxV6xYAZ1OZ/ezybMM0w/Y673lDsu3dhUEEiNCcc2oPi77nPheodh6WIPFm0tNppSTe+0dKb3iWOggV4mOjsaDDz6Mv/zlRknvY0zxXSJ5jxSf7KnEWz+X290vJiwYj182GBOHJBhf0+r02HigSrZzcaWqxlYMjpY+jZy1isDosGDcNDoZd4ztzxE75DeioqJZRnGQvbW+pO5HpuSsxB+XGo+I0CDsrqiDXg/kpMRgdLeRIfbWi5Gjg5dI45HImjWWiK4tZNhPymfJ/QxiDctQvo/xxHFn2sXihOh+RERkSnLjzqJFi2Q/idzcXBw/fhwTJkzA5ZdfjhdeeAGJiYkm+8THx+PkyZMAgOrqaqvbGxoa0NbWZrI9ODgYMTExOHnyJJRKJWJjYxEa+udDolqtRltbG+rq6mwemzxPpNexu1U1tWPl9qOIDgu2O2WQI7aV1Vhcr0GkJ52UHnKO9Iojcsa8eU9ZfF2hgEkeLRVjim+RO08RrWisa+3E3HUlKM5pxMxxgwC4r5JHDomRjk+FlDtYjXGp8Q71oCbyVpZiikIBqNWRDh8zkONJRJhYMVF0P3INSw0Z6389ZWzIEBmREx0W7FQHL3uNKc6OChLp3GdYW0jqZ1U1tlk9pty2Ha5h446PYDyRl2iTDZt2iIgcI/lpXK/XY8uWLSgtLYVWqzW+3t7ejuLiYpMF4kS9+uqr0Gg0WLhwIRYtWoSWlpYeFXuhoaFob+96oLO1vbW11fi3pe16vd7iNsM12PtsKRR+WkdiuC5PXd+lQ9T451XDMW99CbxgjU+Xig4LtrsQ98tbyzA+rWdPuvxDGrxkoaD1aG4acof0LEBJ6RWnUHj+PvAGTAPn0kCv1+OHH7bht9/KoNUaHuf16OjowG+/HXYongD+GVP89R7T6vSoafZsY8p7uyowok8kJgxW4+djtR49F1FJkSqMGRiHutomh48RHKRATv8Y+U7KyzB/ts0f08daTAkOVrCM0o3od/4/w5NQdLxRaD9/uo9EaXX6rmnVzrRD3TsUWf3EGsjl/O3lH7LdkPHPq4bj5a1lNo/x8tYyzLj4bKHP05xph05vet11LR14Yl2J0+cQGRqE0y0dFtMyOEiBy4clWp0yVQFg9oRUKBQQGoFkKDflH9Lg5e+O2L9wmazZdwIXp8ZZXG/Hk/wxHjiL8UScyH0THqJAR5v9ipvwEEVA3IeB/pvj9Zv+N9Dw+k3/KxfJjTvPPvssPvvsM6Snp6OoqAhZWVk4duwYNBoNbr75ZodO4pxzzgEAtLW14dFHH8V1112HlpYWk33a29sRFtbVS1WlUvUIPO3t7YiKioJKpTL+bb49PDwcWq3W4jYACAsLg0qlQl1dndXPliI+3vGeHb7AU9en1ekx4Kx2/O38s/HW9t89cg6W1Ld24uK0ePxwuEa2Y3YKtF6damzDkcYOnJ8ab3xtw/4TeHxtcY/5n6v/KGj9+6+jMXmk6VRyl8VFoM/GQzhZ32px3mgFgLOiw3BZZj+TAom/3+cimAaOpcEzzzwjezwB/DOm+OM9tmH/CTy9rhgn6ls9fSp4blMp/rXtCE42uK8HrzOeuiodQUqFX94XcmMa2eZP6eOKmBLI8aS8SSw/LG9qc6o3uy+yFL/6RIfhqavSezxfW+Psb0+r02PZtp+tblcAeDG/DDVn7I/I6VAohT6zpk2Ha974xeS6bbVRSDmHBz7bZ/zbPC037D+B922shXfPJQMx7YKB2FFWIzQC6UhjB+pb2i2WlSzpHRqEM+1a+zva0dyhwwOr90m+V9zFn+KBsxhPxIncNy3tYj1yW9r1ARVPAv03x+vn9QeyuDh5r19y487XX3+Nl156CZMmTcLkyZOxcOFCDBw4EE888QQ6OjqEj6PRaFBYWIiJEycaX0tLS0NHRwcSEhJw5MiRHvsbho4mJSVBo9H02D58+HDExMRApVJBo9EgNTUVANDZ2Ym6ujokJCRAr9ejtrYWnZ2dCA7uuvzq6mqEhYUhKioKSUlJOHz4sNXPlqKmplHSQse+QqHo+iF64vosjUbxJppGeSspRQsSm/dVoux4HdS9QzGqbxSe/HK/xcKK4bWn1vyKrMTePXqNPTJuEOZYmfJO/8f22tNdPcU9eR94C6aBc2nw1Vdf4cknn8X48bm4+ebr8Pe/P4b+/Qfg+eeflhRPAP+PKf52j+Uf0ljNazyhqa0TTW3yT6vpKkF/jJz2t/tCTsyfbfPH9LEUUwYMGIAXX3yeZZRuRL/zY9VnhI53rPoMNBr7I3z8hbX4daK+Ffe9vxtL8tItjpA3kOu3t+tYnc3OEXrAbqOKQYheZ3fas+iwYCz79lCP1231Q5NyDt11T8txafFWyzUGn/xSjjtz+qHseJ3Q8Usra7H8+9+EGnaAP8tjSoXt6xUleq+4iz/GA2cxnogTuW86BO+rDj0CIp4E+m+O18/r5/VH4vTpRlkbeMS66XTT1NSEkSNHAgCGDBmCoqIiBAcH495778W2bduEj1NRUYEHH3wQp06dMr62f/9+xMXFITs7G7/++qtxuCkAFBQUICMjAwCQkZGBgoIC47aWlhYUFxcjIyMDSqUS55xzjsn2wsJCBAcHY9iwYRg+fDiCg4NNFosrKCjAOeecA6VSiYyMDJufLYVe77//PHF9W/4oTHlrww4AdDrfqcshb/5UjgVfHcB9nxbhyhU/CfVa21NR3yONJ/yx0Hai2RRtSZEqLM5Lx4TBao/fB972j2ngeBqcOXMGQ4emQ68HBg1KQ3HxrwgKCsatt94uKZ4A/h9TPP0dy/mvU6vHS3amTSHbqv/I4z39XXr7P6ZRYKWPtZjCMoop0fTsrRLrA9hbFezx795d/0Ti19KtZejU6l3+25NzvbrECBVm56bJdjy5LN1ahoJjdXbLNXUtnXjjp2NQ9xabYnrHb6cdKk/KPR24yL3irn+A58/Bm/4xnogTSU/R2YcUgsfzh3+iaeev/3j9nj8HXr/nr19Okht3UlJSUFzc1Vtp8ODBKCoq+uPE9GhsFG9lP+ecczBixAjMmzcPhw8fxrZt2/Diiy/ivvvuw5gxY9CnTx/MnTsXpaWlWLlyJYqKinD99dcDAK677jrs3r0bK1euRGlpKebOnYt+/fph7NixAIBbbrkFb7zxBr799lsUFRVh4cKFmDZtGsLDwxEeHo5rrrkGCxcuRFFREb799lu8+eabuO222wDA7meTZ2h1ertzKHtaTFgwTjW02N/RxepaxXqfWysU5g5WY+3dY7Fi2ig8d+UwrJg2CmvuGmNzoVMiR/Ttm4zS0gMAgIEDB6Gk5Nc/tkiLJwBjii8prKz36kZ6XyBagUUUSKzFFJZRHDMuNU7W/fyBSPw61diGwsp6i9u0Oj12HavDmsJK7DpWB60TrQWia2XGhNlupEuKVCEzORq5Njp43XPBANQLli8s6R0iucoBQFda7iqvE9r3492VOKdPVI/zt+SbEtvrmbqLrXuFPIvxRF6i0wVJnlaIiIgAAAq9Xlp70erVq/HCCy/g+eefx9ChQzF16lRcf/312LNnD2JjY/HGG28IH+vUqVN49tlnsWPHDoSHh+Ovf/0r7r33XigUChw9ehTz58/H3r17MWDAAMybNw8XXHCB8b3btm3DCy+8gJMnTyIrKwvPPvssUlJSjNtXrlyJt99+G+3t7Zg0aRKeeuop49ykLS0tWLhwITZt2oSIiAhMnz4dt99+u/G99j5blEbjn8PMFApArY506/UVlNfhvk+L3PNhAWLFtFHITolx+P2euA+8DdPAuTRYt+5LvPrqUjzxxD+QmjoY06f/FVOmXI39+4uQkKCWFE8A/44p/nSPbSypwoKvD3j6NHxWUqQKa+8eg6TEKL+6L+TG/Nk2f0wfazHlwIFfWUbpRvQ7v+P9Auw/ZX9qtpFJvfHWX7MlnYOvEo1fz105DJcPN53eKL9Ug6VmU0snRoRidm6aQx2otDo98lbttNnYlBSpwsPjB2HuuhKr+yzOSzf5fK1Oj8LKemia2qGOCEVmcjS+PVjtsbg9/bwUvPFTudC+/3v9OWhq1+JxL5r21R5L94q7+WM8cBbjiTiR++bcpd8LH++X2ZdIPgdfE+i/OV4/r5/X3zUtnZzrDklu3AGAX375Bb169cKIESPwww8/YPXq1YiJicHMmTOhVrN3v4G/3qye+DF+U3wKT35z0D0fFgCSIlVYc9eYHmvumLNUwDO8J9AzZYBpADifBoWFuxEe3gtDhw7Dzp07sG7dl4iOjsacObMZT7rx9Xuse15S09yOZd8dsf+mADUuNR7bymqsbl+cl45Lh6gDPu+xh/mzbf6aPuYxZf36L5GYqGYZpRvR7/ziV35Aa6f9HcOCFfjh7xfLcGbeT7SzmXkHqvxSjc0GB/MGFlGix7XUsJQUqcKsCalCn+vJTnb/e/05mLu+BA0CI4d6hShx9Tl9oDnTji2HqmWfRs0VpHS2s1Uuc4a/xgNnMZ6IYeOOdIH+m+P18/p5/fI37kge+Xjy5Emce+65xr8vvvhiXHzxxdBqtXjvvfdMegMQOUur0+Otncfw9s9iPbYcFREaBK1ej5YOnUs/Ry69Q4JwpsPxBX5mTUi1WxiQu4chkbmqqlPIzBxt/Hvs2PMxduz50Om0WL/+S8YTP2EpL5FrUWJ/khShwqzcroq2bw9WY/GWw6hr+XPRXikVcUSByFJMOe+88xEb24tlFAeI9v9zoJ+gz8pMjkZiRKjd0TKZydHGv0Wmln5h0yGMS43v8WxurzLfMJWavYab3MFqjEuNd7hhQOS6ReN6bHgIHhk/CPG9Q7HwmwOoPmN9cfqkSBWyU2Jw8+hkvLb9qN1jN3fo8NHuSvsn4SXM7xVbWC5zL8YTIiLyJZInwL3lllvw+++/m7y2a9cuXHvttVi+fLlc50WE/FINJv17B17bfhRtna5tdGlq13p9w060Kgh3jEnB9PNScNf5/YXeExMeYvJ3UqRKqHegoSegeSGuqqkdj68tRn6pRtrJE1nwwAN3obz8mMlre/cW4s47/8p44ies5SVs2DF17wUDsObuP9c2mzg0ARvuO89r1z7T6vQoKK/DxpIqFJQ7t24EkVysxRSWURyTHKWSdT9/EKRUYHZums19zDtQiazTU9/aiTd3mt67+aUa5K3aifs+LcKCrw/gvk+LkLdqZ49ncNG1MoOUCmSnxODy4YnITomRNOJD5LqfnzIcj4wfZPdYtS0dSIxUYcyAWDx66WCb+xrS8o6x/RFlZ+0guSRGhLrts0Q62wEsl3kC44m8gmTej4iITElu3Lnssstwyy23oLi4GDU1NXjsscdw2223YcSIEdiwYYMrzpECkOEhVmQIfqCob9PirZ/L8cZP5Xjl+9/s7p8UqcJX99gv7JkT6WH48tYyVuaR08aNm4AHHrgLhw4dQG3taTz77D8wc+a9GDJkGOOJHxDJS2SYTcQvfGyhp7EzFXGuJFrhSORulmLKQw/dyzKKg1raxZ7BRffzF4bRMokRoSavW+tApbHTsGPw8e5K47O1vcr8bw9VmzSwA3A6XthrtLd33ROHJCC+l+k2awxpIpqWQUoF5k8aIvmaHKHX63H1yLNc+hmine0Alss8hfFEXqLzjTg+LwkRUWCT3C1l7ty5OOuss3DbbbdBqVRi4MCB+PjjjzFq1ChXnB8FIJGHWLJv1oRUhAYrhedxNhDpYXiqsQ17KuoxOTHKiTOkQPfQQ7OQkJCImTPvg0KhRP/+A/Dvf7+BESNGQq2Wb/5R8gyRvESnB64Ynog+USro9Hq8/XOFm87Ouxh6bd99/gBPn4pN1tZ3MFQ4OrpuBJEcLMWUFSvewCWXnO/pU/NJp86IVbOJ7udP7E1zZr7OnIiG1k4UVtYjMznabjlo/voSkxGwzk7PJTrll63r1ur0wtda09wOrU6PIKVCeMo4Q0PQ85sOubTzX/WZDry3qwK35vTDxgNVdp9jpLghsy8uHaKWNCWeaLmssLJecpmPrGM8ISIiX+LQmOM77rgDSUlJmDdvHu666y427JCsRB5iyTqlomtqBEcLeKI9DDVn+B2R82666a9ISEjCokVP45ZbbkN6+khPnxLJRDQv+aakCkDPaSQDzUcFFbhzbH+vGaFjTrT3sKV1I4jchTFFPqKTFXv3pMauYxhdac5SQ4kCgMi4Ck1Tu3DHiO6kNLCbr+NT29KBuetKeuxn7ZiWrtvSNduy7Lsj+GBXhbHxyFpamssdrEZkaBAe+Gyf0Oc4Y9PBavxn+hjsO9EATVM7jtW14JOCCtS3Od6YeekQteQGGOFyGcvOsmM8ISIiXyHUuDNs2DAoFD0L6nq9HjNnzjR5raSk58MhkRR8OHWOTt+1WKmj1BFiUyqoe4vtR9TdxRefazWe/OMfj5u8xnji20TzEoO6FuuLKgeCxjYt3tp5DHd56egd9h4mb8SYQt7E2uhG0Qmz1BGhTpWD7DWwW2qEsdcWL3JMS9dsj6MjPkenxCAxItTlHQFPNbZh34kGk3hW39qBT3Yfd+h4SZEqZCZH92hcszeKR7hcJvGZi3piPCEiIl8l1Ljz7rvvGv9fr9dbDHpEcuHDqfOcKRhmJkfbLTQlRaqQ1S/a4c+gwPXqqyuM/28tnigUQHR0L3eeFrnAOX2ioFT07GFM1r22/SgGqXt75dRm7D1M3sheTGE8cVyvIKBZYJBCL66ADcD5aaUNlf+FlfUOH8NWA7u1Rhh7MdrWMeWYSlvqiM8gpQKzc9McalCSqns80+r02Fhc5fCxZk1IxbayGqHp77oTKZcl/tFIRM5hPCEiIl8l1LgzZswY4/9PnToVixYtwtChQ112UhTYRB5iyTZnGshECk2zJqRy2h1ySFZWtvH/77zzr5g/fyFSU9NM9lEowDV3/MC+Ew1s2HGAt05txt7D5I3sxRTGE8clRKpwtK5NaD9yflppw7O1s+UgSw3szjbCWGu0l2MqbUdGfBrX39l4EA1OTJNmT/d4VlhZjzoH1vpJilRh1oRUAHBozTqRcllbpw7bymq8smOIL2E8ISIiX6WU+oaqqioEBbGLFrnWtaP6ePoUfJYcvbcMhaZEs0q6pEgVF8wm2dTUaKBUSg5D5CM4gsMxhooub2OocLTF0POcyBMYU+SlChZLS9H9/J1ozItSmZajzZ+tDZX5jrLUwO5sI4y1Rvtth2scPmZ3VY32GxHN5Q5W45956Q59XpQqCL1CbNdnRIcFm8QzKc80U0Yk4ZkrhmLFtFFYc9cYjEuNF1qzTmulR4yhXBYVZrlfbn1rJx5fW4z8Uo3wOZJtjCdERORLhEbudHfNNdfgrrvuQl5eHpKTk6FSqXpsJ7LH2nzDUhfkpJ7k6r2VO1iNcanxkuaFJpJi8uT/wezZD+Hyy6/EWWf1QWhoV+WBQgFERoYznvi4uF6Or/3lb1RBClycGo9vD4lVvHhjwxhHdZK3sxRTDPEEYBlFqmDB37Lofv5OdNTiP/PSERvTG2XH66DubfnZ2lCZL7VMZK2B3ZmYYu2YWp0e35Q4Pk1Zd7US19wzliPPtCOudyhOn5F2fddm9MHqPdLWzpEyKnX9r6ew8/fTePTSwQhSKlBQXuf0mnXjUuOxNFiJBhvH8NaRv76I8YSIiHyJ5Madr7/+GkqlEuvXr++xTaFQMNCRXZYacBIjQnH5sES8t6vCg2fmHwy9t24enYxxafFONcgEKRVcGJtcJj9/M4KCgvDttxt7bAsKUjKe+DjOyPan+ZOG4Ir0JAzacRQrtx+1u7+3Tm1mrcLRMO2MpU4FUhePJnKUtZiiVCpYRnGAaKMCO2R1EV2zMjslBkmJURgcHQq9jUCZO1iNosp6fFBQKXwO1hrYnYkp1o5ZUF6HOomNMtbEhtvvDGKIJdsO1+Cb4lMOTZFm8M7P9sub9a2dJo0tmcnRiAoLRoPg51af6TBOt1ZYITYa11YjnMjoK0emuCPLGE+IiMiXSG7cyc/Pd8V5kJ8yr9Spbe7A3PUlPfarampnw47MPtpdiY92V9pdqNNXsILQ/6xevdbi65zT2j/UNstT6eMPEv9Yk+LOsf3xZdEJu5V/mcnRXpvnSRnVaa0zhz/EJGu89XsLBJZiCuOJ45raxCqxRffzd3KPbvz2YLVww461BnZDflTV2IaY8BCbjTFKBUzWybPVaJ9fqsHzGw8KnZuI2pYObCypQlyvEOjR9fzgDTM7dG9s2VZWI9yw093S/MNo14p1d7HVCCc6+sobR/76IsYTIiLyJZIbdwCgsbERa9euxe+//477778fe/fuRVpaGlJSUuQ+P/Jhlh7EWb/hfoaFOhdNGY7YXiE+WeEUiBWEgaKpqQkbN36Niopy/O1v0/Hrr/swcOBAqNXDPX1q5AStTo+aZlYwAEBSxJ9T2ohW/m0rq/HqPE9kVGd+qcahxaN9GWOV55nHlOLifRg9+hyWURwguk69C9ez9zmOjG60RKvTY/EW22u0GDwyfhBuzEru8UwvtUHk+f/pWU4AukbodH9tW1mNzRhmLiYs2OYoG6UCWPbdEcvvDQ/ByLMi8eNvp4U/r/txrSxhI6y8rgVA1/dhb80ca0TTPzY8xOaadaKjr6ztx44H0jGeEBGRr5DcuHPo0CH87W9/Q58+fXDo0CHcdttt2LRpE2bNmoXXXnsNY8aMccV5ko+xVqnj7EM2OW7+VyUm6e8rFU6BWEEYKI4cOYyZM+9HUtJZKCsrxfXX34ht2/KxcOEWrFzJeOKruHaaqVHJUSYVKPYq/wDYzfMuHeLdeZ5IRZi/rQ3AWOV51mPKfJZRHCD6yM5H+54V5/+ZPgb7TjQ4XJFeWFkvPOVZfK9Qiw07og0w1hqerDVWt3aIt+ZFhwXj8csGY+66nrM2GNgqG9a1dDjUsNP9uLmD1cgvFVvvztyXRSdxx9j+QlOiOWvy8ESb94jotH+WGojY8UA6xhMiIvIlSqlveO6553DzzTfjiy++QEhI1/y4ixYtwi233IIlS5bIfoLke5zp3USuY154MlQ4OVrgcQfRCkItWw190r/+9RKuvfZ6vPHGewgJ6eppOG/eU5g69XrGEx9lqFBiw86fNh+s7pHP5g5W4z/Tx+CR8YNwQ2ZfPDJ+EL6489yuBZP9IM+TsjaAP2Cs8g7WYgrLKORK+aUa5K3aifs+LcKCrw/gvk+LcO0bP6O+tROXD09EdkqM1Up7rU6PgvI6bCypQkF5nTGPkDK1lvlIDZH8KDY8BM9cMRQrpo3CmrvGWGzYsRTLq5ra0SBhqFZ9ayeUCgUW56Uj0ew83dWsv6u8zuH3nmpqMzbaudq4tHib2w0jf22xNO2fre/S28uBnsR4QkREvkRy486+ffssLiB300034fBhVuiTWKUOOa93iOSfr0XeXOEUaBWEgaakpBiTJ/9Pj9evvnoq44kPYsO+dUvzD5vks/mlGlz7xs9Y9t0RrC48jmXfHcG1b/yMt3YeE8rzPt5d6bX5NhB4awMwVnkHazGFZRRyFWcqzvMP9WwUylu1E/mlGhz7YzoweyxN5SWSH9W2dCAxUmWx4Umr0+OFTYeEPl+EYZTmIxNSERP256Qh7opgjqyT051h9JWjEnqH9GjYMmdtxI05w8hf8+MlRaosjg5lxwPHMZ4QEZEvkTwtW1xcHH777Tf079/f5PXdu3cjPt52jxMKDP5SWeMpSREq6PQ6VJ+xPh1DYkQozu0fg6+Kq5z+PEOFk731Ezwh0CoIA01MTCyOHTuK5OR+Jq/v31/EeOKD2LBvXVVTuzGftTV912vbjwodb9l3R/DWznLcmNUXd4zt73VTmzm7NoCvYazyDtZiCsso5ArOTD+5Yf8JzLExjaOoORPTehzb2fzozZ3HUO9kg0h3pxrb8NbOY8LxzRV6hwbhTLtji0P9dvoM4nqF2J0SzZprM/oiVd3b7lp7onE8d7Aa41LjhdbPEe14sKeiHpMTo4Q+P1AwnhARkS8Ratzp6OgwTsF29913Y8GCBbjvvvug1+vx008/4T//+Q/eeecdPPLIIy49WfIN/lJZ4ymzclOh0+kxd731+amrm9pladgx8NYKp0CrIAwEnZ2dCA7uCj1/+cttWLz4Odx66x3Q63XYvXsXNmz4Cp9++iFmzZrl4TMlqaoa2zx9Cl5N09Qu6+imupYOvLb9KD7eXYl5k4Z41bz5zqwN4IsYqzxHJKasXv0RyygkOykj9rp3oNLq9Hh6nXgDjjW35vTDxCEJPV53Jj/S6vT4uKDC6XMz99HuStmPKcUt2clYteOYQ+9946dyvIFy9AoNcuj9/WPC7a61JzV+BykVQp3yhBv6znhnOdDdGE+IiMhXCTXuXHjhhZg8eTKmTJmCm266CUlJSXj99dcRFhaGJUuWYODAgXj22Wdx5ZVXuvp8yQeIVOqQZVNGJAEAln1XZnF7r5AgNHdoZZ/KwFsrnAKtgjAQXHXVJEyYcCkuu2wyrrnmOiQkJOLDD99FWFgY/vd/X0H//gPw+OMLcOONUz19qiSBVqdH0fEGT5+GV4vtFeKS0U31rZ14fG2xxSlZPMWwNoBcPZW9HWOV54jEFJZRyBUcHSGzp6IeJ+pbnfrsu8/vj3suONviNin5kVanNxkBotPpJa2pI8rZqdGcYYgyFw2Mw4+/nXb4OM0OjvwxlLGkjLiRy7ayGrFz7O2d5UB3YzwhIiJfJdS4s2DBAmzYsAF33XUXYmNjceWVV2L+/PlIT0939fmRDxKp1KGeFADOHxhrM92aO+QvcHlzhVOgVRAGgkceeQxbt36L2bNnIiYmBrm5l+Hvf5+NIUOGGfdR8Ov0Kfmlmh69UaknBVw7StLa9D+eIndPZW/GWOU59mKKQgGo1ZEePkuSyrzRwdWV4I5wdISMHKMkBsT2srpNND/aVlbTI3+OCpM8Y7tdkaogNLqgwUiUHnB41I6zkiJMy1iiI27k0N6pw5ZD1Xb3S+gdgqx+1suBvvBblAvjCRER+SqhJ7i8vDzk5eWhqakJ3377LTZs2IAbb7wRKSkpmDJlCq666iqkpKS4+lzJh1ir1CHrbslOxivfHXH753p7hVMgVRAGgkmTrsCkSVegufkMvv/+O2zd+i3uu+9O9O2bjIkTL8dll01Gv3797B+IvIK19WOoJ82ZdiRGqoT2veeCAXjvl3K0dOiEj3+qsQ2f7KnEjVnJAOAVlTGe6KnsKYxVnmEvpkyaNBlq9XBPnyZJYKnDQGJEKGbnpnnV70hkhEzv0CBUNbahoLzOmPdtOyw2msIWew1L9vIjABZjtytG2HRo5Z5vwHfMyvVcGeuzvcehE0j6sWfHWT1HX/ktyoXxhIiIfJVCr9c79MTV1NSEzZs3Y8OGDdixYweGDh2Kq666Crfddpvc5+izNJpGOJa63s3Qa0Xk+rr39jlScwZv7ix3z0n6mIsGxuGv5/bDfZ8WueT491wwAF8WnZC1wknKfSAHb+w55u408EZypMGZM03GQtSuXb8gLS0N1157DeNJN954j2l1euSt2skGfEGPjB+EG7OS7aZZUoQKM8cNxPyvDjj0OVFhwVAAJgti+3NljDWeyp+9MVZZ4s/xyzymDBvGMkp3ot/5uUu/Fz7mL7MvceKM/mSvw4A3TT8JSOvgkBgRisuGJuCDAufWn0mKVGHNXWOE8hVL+REAt8Tu8GAFWjr9LHMR1Ds0CE9OHurRe3XJlsNYXXjc7n43ZPbF4xPTesQDX/stugrjiX0iMcUT8cSb+fMzmAheP6+f1x+JmppGxMfLNxrU4cad7n766ScsXrwYBw4cQEmJ9UXgA42/3qyO/hgLyutc1njh6/73+nNQc6YdT35zUPZjGwqBgLw9uQM9UwaYBoD8abB79y4sX74Mhw+XMp504433GPN0aZ65YiiuSE+yW2ESqQqCTg+ccXB+f1sCpTIGYP5sT6Ckz+7du7Bixasso3Qj+p2PXfo9RMYOKgHslKEyTqTDgJSGDXfQ6vSY9O8dbl1Txtl83B2xe2SfCOw/0eTSz/BW4cEKfDvjQoQGKz3a2P9hQQWWCcwI8cj4QfhLTj+TeOCLv0V3YDyxjI070gXKM5g1vH5eP69f/sYdhybW1ev1+OWXX7Bp0yZ8++23aG5uxsSJE/HYY4/JdmLk+7o/0Mb1CoFWr0dUWLBHF9X0Vgu/OYCxZ8e55Njdp11z1zzPRKL0ej0KC3dj27Z8fP/9d2hpacG4ceMxd+4Tnj41ssOV68f4o9heIQD+nC7nhU2HTEbXGLhybQJvW5eHSG6WYsqkSZexjOIA0UkhxSePtK2wst7uaJJTjW0orKz3mufZwsp6l5Rrbh6djC2Hql0yxaM7YnegNuwAwMShiQgNVnp8SrPrM/rilW1HbE7NplR07WfOF3+LrsB4QkREvkK4caezsxPbt2/H5s2bsWXLFjQ3N2PcuHFYsGABLrnkEoSGii0qSYGBC2xLU32mA+t/PSXrMaPDgjFv0pCA6aVNvqOzsxO7dv2Mbdu24scft6GlpRnnn38RHn74MZx//oUIDQ3hgqU+QHQxaepSVn0G5/3RiD8uNR4vBbm/gSUQKmMo8NiKKRdccCH69HFN5xmSl2ijgzd1LHDVuYxLi8ffxw1yyagP0ditABCAHWqddm7/GKsjdKua2vH42mK3jKINDVbiL9n98N6uCqv7/CW7H0KDlT1e98XfolwYT4iIyBcJNe489thj2LZtG5qbm3H++edjzpw5uOyyy9C7d29Xnx/5IC6w7R0WTRmOcwfEAvCdNQDI/z377D+wfft/0dLSjJycMZgx4++45JIJ6NWrl6dPjSQSWUya/rSnsgE3ZesRpFSgsLIe1Wc6PHIe/lgZQ4HLXkxR8FHHZ4g2OnhTxwJXnEtseIhxbRxXEIndseEhqG3xTIzydereoVi4wfY02+4aRTtz3CAAwAcFFSYjeJSKroYdw3ZzvvhblAPjCRER+Sqhxp3jx4/j4YcfxuTJkxEXx94KZJ1Wp8fS/MOePo2AlxSpwug/emZ7eloAou5OnjyJe+55ABMmTERMTIynT4ecEKRUYHZuGhvzBW0rq0Heqp2YnZuGjk65JjKSzt8qYyiwMab4D5FGh6RIlUsbPqRyRSeHORPTsK2sxmXP7iKxe/LwRHy0u9KpzwlESZEq6AGvmtJs5rhBuO/Cs/HZ3uOoqGtFv5gwXJ/R1+KIHQNf/C3KgfGEiIh8lfWo3s0HH3yAW265RfaGnVOnTmHmzJkYM2YMLr74YixatAhtbW0AgPLyctx+++3IzMzElVdeiR9//NHkvdu3b8eUKVOQkZGB2267DeXl5Sbb3377bVx88cXIysrCvHnz0NLSYtzW1taGefPmIScnBxdddBHefPNNk/fa+2yyTmSOXnI9wzo7hlFU5t+JYVqA/FINtDo9CsrrsLGkCgXlddDampyZyEn/+7+rcO2118teaGI88QzD+jGJbDAQYsh7y+ta7O9sw1+yk9EnOkzy+/yxMoYCG2OK/8QUQ6ODLd3XkfQGIucsxbjUeCgVCpvP7t8erHb5c3t9C8tyjnh43CDsrqgT2tedo2hDg5W4Jbsf5lyahlusTMXWnS/+FuXAeOI/8YRci/VHRN5HqHHHFfR6PWbOnImWlhZ88MEHWLZsGbZu3Yp//etf0Ov1mDFjBtRqNT7//HNcffXVePDBB3H8+HEAXSOJZsyYgalTp+Kzzz5DXFwcHnjgAej1XZnKxo0bsXz5cjzzzDN45513sHfvXrz44ovGz16yZAn279+Pd955B0899RSWL1+ODRs2GM/L1meTdVqdHqsL2cvL0+65YAByB6uFRlG9sOkQrlr5E+77tAgLvj6A+z4tQt6qncgv1bjpbImcx3jiOVqdHtFhwRwFKNHHuyuR0DvEoffefV5/PDIhFU9dlS75vf5YGUMkN8YUz7HWYSApUuWWdUocIWcnh5JTjXaf3eetL7H63C5S4SZSPvi6pNrxiwhASZEq3JrTD8u+K8MbP5XbfwO8fxStL/4WvRHjCfmb/FIN8lbtZP0RkZcRmpbNFY4cOYLCwkL897//hVrd9XAwc+ZMLF68GJdccgnKy8vx8ccfo1evXkhNTcWOHTvw+eef46GHHsLq1asxcuRI3HnnnQCARYsW4cILL8TPP/+MsWPH4t1338Xf/vY3TJgwAQDw9NNPY/r06Xjssceg1+uxevVqrFq1CiNGjMCIESNQWlqKDz74AJMnT8ZPP/1k87PJsvxSDZ7fdAgNrZ2ePpWAlhShwp1j+wMQG0VVb+H7cudin0RyYDzxDEtTPpKY+tZO3H1+f6zacUzye1NiwwEAk0f2wZK8dLxk9h1EhwUbP8MgKVKFWRNSmacTCWBM8QzD+pAdnTo8NXkoFABON3f4xFqRuYPVGJcab1zfsryuBf8pOmGSN4usYyMST82bawzP7bfm9MPGA1Umx4gJD8Hjl6Zh4tAE42ucZUE+089Lwbn9Y1Hb0oG560qE3+cro2jN72tf+C16G8YT8ifW1tZm/RGR53mscSchIQGvv/66McgZNDU1Ye/evUhPTzdZYDs7OxuFhYUAgL179yInJ8e4LTw8HCNGjEBhYSFycnKwb98+PPjgg8btmZmZ6OjowIEDB6DX69HZ2YmsrCyTY69YsQI6nc7uZ1NP1jJ5cr9ZuX/2ynZ2uL+7Fvskchbjifsx33eeTq/HoquGY/76EkiZzaB75WDuEDUusVDxAoCVMUQOYkxxP1vrQ7pjXRI5BCkVJud6x9j+JvlwVWMbnvzmoMs+/71dFT1eq2vpwNz1JSg+2YiZ4wYBcO90YAY3j06G5kw7Nh/0nxFBSZEq3H3+2QCAvFU7Jb3Xl0bRmt/XJA3jCfkLkVGfrD8i8hyPNe5ERUXh4osvNv6t0+nw/vvv47zzzkN1dTUSExNN9o+Pj8fJkycBwOb2hoYGtLW1mWwPDg5GTEwMTp48CaVSidjYWISG/jnEWK1Wo62tDXV1dXY/WwqFn+ZphutSKMQyeZJPr5AgXJfRp0fPvKRIFWZPSEXukD8fHJ0d7m9Y7DOnf4zF7d3vg0DFNHBNGkg9FuOJe2l1eryw6ZCnT8Pn6dHVk1vqNNWxvUJMfnfBQQqL+bS1vDtQMH+2LVDSx5Hr8/eY4orv3Jlj5h+y3RN4SV66yfOtrzDPm3cdq/PYuby3qwIj+kRi4tAEt08HFhUWjKx+0cbv0F8aeCYNTUBwkAK7jtUJj4SyVF7zBoESD5zFeGKZ3PdNINyHvvibExn1aa/+yMAXr19OvH7T/wYaV12/xxp3zL344osoLi7GZ599hrffftskEAFAaGgo2tu7MpOWlhar21tbW41/W9qu1+stbgOA9vZ2m8eWKj4+UvJ7fEl8fCR2lNVwaL8brbotBxcOVmOhTo+ffzuNqsZWJEaGYczAuB49JC6Li0CfjYdwsr61xxQOotqUSqjVtu9jf7/PRTANvCsNGE9c67+HNRandCRpLh3RF5ozbZLfNzg51ng/eNN94a2YRrYxfezzt5jiiu/c3rOiNVqdHsu2/Wx1uwLAsm1HcN15Z/t8T+DcmN6I+6oEp89YnppNASApSgVAgZMNrbJ//uIth3HD+QNxWVwEztpwECcbpMcfRzS2duLxtcX431uy8Nfzzsb3hzVo0/r+4tvflmqwcOootFU0CO3/4IRUPHLZUK++jxkPXM/f4gkg/33jaDzxRb70mxPN60Tqjwx86fpdgdcf2NcfFyfv9XtF486LL76Id955B8uWLcOQIUOgUqlQV1dnsk97ezvCwsIAACqVqkfgaW9vR1RUFFQqlfFv8+3h4eHQarUWtwFAWFiY3c+WoqamEXrff3btQaHo+iHW1DSi7Hidp0/H5ykVwC3Zydh0oNpmQ1lSpApp0aHQaBoBAIOjQzE4uuuhrPZ0k8X3PDJuEOY4MXWSSqczfp657veBP97nIpgGrkkDwzEdwXjievn7udiqs6LDgpEWHYrGxhZJ70uKVGFQZAhqahoRExuBb/dWoLqpHereocjqx6nXumP+bFugpI8z8QTwz5jiiu/c2rOiPbuO1eFEvfWGDD2AE/Wt2FxY4dOjEfMPafBS/mGrDTtA17XOGp8KAE49u1tT29xhTMerRiQ5tOabIwy32gMf7nHL5zlCgZ5rGdljuC9VgvuPTOhttbzmaYESD5zFeGKZ3PeNo/HEl/jib06l0wnvZ+879MXrlxOvn9cfHx+J06cbZW3g8XjjzrPPPouPPvoIL774Ii6//HIAQFJSEg4fNp3qS6PRGIeOJiUlQaPR9Ng+fPhwxMTEQKVSQaPRIDW16wG5s7MTdXV1SEhIgF6vR21tLTo7OxEc3HX51dXVCAsLQ1RUlN3PlkKvh1/frHo9oO7t3qH9/kinB97fVYlbc/pZnC/bYNaEVCgVCkn31ITBaizOS+8xj3lShAotnVo02Oh9b1js097n+ft9LoJp4B1pwHjiWobFrnf8XufZE/ED8yYNgVKhQGZyNBIjQoVHwBriwJaDGizb9rNJpahhfQouZGrKG3473ozpY52/xhRXfOeOHk90/RdNU7vP3qcia9QlRarw8PhBiAoLhqapHf+TnoiviqtkPxdNUzu2HNLgk92Vsh/blzl6a2ma2jFxaILdOC5apvI0xgPX8dd4Ash/3wTSPehLvzmRMovUvM6Xrt8VeP28fjkp5T2cNMuXL8fHH3+Ml19+Gf/zP/9jfD0jIwO//vqrcbgpABQUFCAjI8O4vaCgwLitpaUFxcXFyMjIgFKpxDnnnGOyvbCwEMHBwRg2bBiGDx+O4OBgk8XiCgoKcM4550CpVNr9bDJlyOTJtktS4xATZrstdc3+k7j7/P5I6B1i8npSpAqL89IdrrDLHazG2rvHYsW0UXjuymFYMW0U1tw9BvMnDbH5Pl9a7JOI8cS18ks1yFu1E/d9WoTik/7fo85VEiNCTfLzIKUCs3PT7L6vexzIL9VgztriHr3dDetT5JdqrByFiEQxpriH6Pov7l4nRi4ia5PGhodg5iUDsWxrGe77tAgLvj7gkoYdACiva8Hja4vR0KZ1yfF9WZQqyG5ZzZw6IlQojrNMFdgYT8gfMK8j8m4ea9wpKyvD//3f/+Huu+9GdnY2qqurjf/GjBmDPn36YO7cuSgtLcXKlStRVFSE66+/HgBw3XXXYffu3Vi5ciVKS0sxd+5c9OvXD2PHjgUA3HLLLXjjjTfw7bffoqioCAsXLsS0adMQHh6O8PBwXHPNNVi4cCGKiorw7bff4s0338Rtt90GAHY/m0wFKRV4ZEKqp0/D641OjkadnTUqGlo7sWrHMSgUCtx7wYA/G2LuGuN0T+wgpQLZKTG4fHgislNiEKRUIPePUT3mjXPONiYRuRvjiWsZeh1zfTXn3Dk2BWvvHtsjb7WWF8eGh+Dm0ckmcUCkovDlrWXQ6gK4GxSRkxhT3Eekk5ihJ7AvElmAuralA/O/OuDyGJvQOwQfc8SOVQ1tWrtlte5iw0OM9yXLVGQN4wn5E+Z1RN5Lodd7ZiDUypUrsXTpUovbDh48iKNHj2L+/PnYu3cvBgwYgHnz5uGCCy4w7rNt2za88MILOHnyJLKysvDss88iJSXF5Phvv/022tvbMWnSJDz11FPGuUlbWlqwcOFCbNq0CREREZg+fTpuv/1243vtfbYojcY/5xBUKLoWujNcX0F5He77tMjTp+W1osOCMXtCKp785qCk97krQBqmWtI0tUMdEYrMZLF1G8zvg0DENHBNGhiOKYrxxHW0Oj3yVu1kw44MVkwbheyUGKvbRfJi0Xhr77MCAfNn2wIlfaTGE8D/Y4rod37u0u+Fj/nL7EsknUN39qYt8+UKo40lVVjw9QFPnwYAYFBcOI6clrbOG1m3aMpwTByaYBK743qFQI+u9Y2klKk8LVDigbMYTywTuW/cFU98ha//5hytPzLw9et3Fq+f169Wd6055Mw6bj2O66nGnUDgrzer+Y/x5a1l+Ig9waxanJeO6LBgyQ1gUWHBWDRluHGkjSs4E5i73wedWucCvK8K9MAEeEfjTiBw1z1mnifodHo88Nk+13+wn0uKVGHNXWOczhdFKwqfu3IYLh8ufd50f8L82bZASR/Gk568rXEH6Grg6bE+ZKQKsyak+mzDDsAOcP7qL9nJeHh8qsX7VnT9O2crR+UUKPHAWYwnlrFxR7pA/82JXL9oHulNeakofv+8flc07kibWJbIjFanxzclrpkX2h+MS41H7mA1vj1YLfm9Da2dmPHZPpctkp1fqsFLW0pRfabD+FpC7xA8eulgSZ+Vf0iDlxws2BCRe9l6ALZUSRElcf55suzh8YNkKXj4+/oURBSYcgerMS413ucqaOzJTI5GQu8Qk2dt8oxeIUo0d+hkOdbmg9VQKhR4b1dFj22G9e+sjTjT6vR4c+cxfFxQYbL2EctORORLXNmoItpw7kwDO5G/Ya0NOaWwsh51LSywWPPDkRq0tGux6NtSh49hr5DgCGtTYFSf6ZD0WRv2n8AcC8dxxTkTkXNsPQADsJgnNEiYf556SopUYdLQBCzbWiZLwcOwPoWtafJ8eX0KIgpchvUh/cm2shq0a+XtlhobHoJalr0kk6thB+gq51hq2Onu5a1lGJcab1LZmV+qwQubDqHewrMVy05E5Ctc2ahirZ7KPI8U3Y8oUCg9fQLk2zRch8EmnR54fO2vslSQyrVItlanx/ObDtnc54VNh+x+llanx9PrrM+RDnBhbyJvYXgANm8UMDwAv2AnTyAxiRGhuOeCAXjuymFYMW0UHh43CO/tqrCa7vmlGknHD1IqjI1x1vrGzZqQ6vO93YmIfJ0h7lqqyAe61uRcNGW43RGyUaog/O/15xjjyuT0BFecbkCIDgtGQu8Qt3zWqcY2FFbWG/+2dz8YsOxERN5Kq9Nj1Y6jNsuUUss25sdfmn/Y5j4vby1De6dOaD/mpRRI2LhDDtHq9Nh1rA5bDnFKNnsKKurt7yTAvJDgqN3ldXYbm+pbO7G7vM7mPnsq6nGivtXmPnKdMxE5TuRB2V5lA9nWOzQI/3f9OfjP9DEY3a9r1IxOp8ey78psvs+RgkfuYDWW5KXjrOgwk9eTIlXspUZE5AVE4m5YSBCgsD9CtqFNi6Z2LS4fnoiaM+34qOC4nKcaUOpbO7Hwiq5Gshsy+7r88wydIEXuBwO5y05anR4F5XXYWFKFgvI6VnYSkUPySzXIW7UTK7cftbmfM40qhZX1NmcnALryyM/2Hhfaj/VQFEg4LRvZZGkuze/LarBs2892K/api5zTMcgxUmqXnUab7vudOyDW+rmcETsXju4i8iyRB2Vyzpl2LQqPN2DhhoOS0tpQ8JA6FVHuEDWuO+9sbC6s8Kv1KYiI/EFBeZ1QxdPizWLTNv9zcykKjtVideEJOU4voNU2d+Dy4YkAgNWFrm0oM6x/J/U5TK6yE9ejICI5WJsCzRJHyzaAeN5XUSdWD8l6KAokbNwhqyw9EEaHBbOHtwQKAHL2j5JjkWyFYN2fvf3Uvbmwtzdy5eKG5Jv4YOse9nqyWePo9xOkVCCnfwz07IRLfowxjXxNfqkGC74qEdq3TrBMVdvSgU/ZsCMLQ7lEZA07Z3Rf/05qnJej7MT1KIhIDlJGHho4WrYRzfv6xYTZ30nC8Yj8ARt3qAetTo83fjqKVTuO9djGhh1pJg5RY/Mhx+cd7U6uRbJH94vBGygX2s+WrH7R6BMdZnMEFxf2di/20CNL+GDr3fj9EFnGmEa+RkrvZnK/7uUSwxp2rvq+uq9/JyXOy1F2El23YlxqPBvLicgmR2aAiO0VgoLyOskdc0Qa3ZMiVbg+oy8+sLCmqfl+rIeiQMI1d8hEfqkGl/3fdosNOyTNrTn9sPCKYZDrmXnS0ARZHsCzU2IQbWfx1uiwYLtDaYOUCjx1VbrNfbiwt/sYKhRcsbgh+TbDg7It9vIEcg0WPIgsY0wjXyO1d3N4CIvh7mZeLskdrMbivHT0Cgly6HiXDU1AQu8Qk9csrX8n8hxm7RwdIbpuBdejICJ7pI7CiQ4LxsJvDuC+T4uw4Ouu/+at2in03GZodLdl1oRUhAYrhfZjPRQFEj5VkpGhIN3YpvX0qfi07JRo/PfvF2HmuEHYd6IBcq1b+d6uClkqM4KUCsybNMTmPvMmDREKhpNH9sGSvPQeBRYu7O1eoj30uIhqYBJ5UJ43aQgWW/gtk2ux4EHUE2Ma+SKpvZszk6MYc90kNjzEZrmkucN62XdcarzV72nzwWooFArce8EAPHflMKyYNgpr7hrT43NEnsOiw4JlKzuJVsZy2l4iskfqDAP1rZ2oPtNh8pqUjjmGRnd79Uui+xEFCnbVJQBdBemXtogt6kk9hYcocff5/TEkIQJ1LZ3Yd6IBmcnRsj80yzWE3hAMzac7SYpQYVZuqqRgmDtEjUtS4zknvgdJ6aHnyOKG5Pus/uYjVZg1oes3n1+qwZm2DhtHIblEhwXjptHJGJca7+lTIfI6jGnkTnKt6yT1mf+8s+Nwzai+nMbNhqRIFR4ePwix4SGoamzD4m9LcaZDJ/k4j4wfZLFsI9KQfKCqCf+ZPgbv/FJucW29qqZ2vLb9KBbnpdvMj6w9hxmeB+4Y21+2spNoZSynhSVfw3X43E90fbLE3qFo1erQYGMZB0NdVnCQ7e8sd7Aa4wTql0T3IwoEbNwhAF0FafMWdhLX0qHDuz9XmCyMmhgRimtG9ZH1c+SszJAzGAYpFaxg8SD20CMRtn7zXCfAtRIjQnH1yLPwyZ5KNLRpUd/aide2H8V/ik7gkfGpiO0VwkIJ0R8Y08hdnF3XqXtFY02z+P2oVAA3ZPZFSJASt+b0wwcFFbKN9PcXj4wfhBuzkk3iYUiwEnPXlUg+VmKkyuLrUhqSvyw6YXM/kQ547qqIFF23gtPCki/hOnyeIbI+2b0XDEBG3yg88Nk+m8cy5Kc5/WOEPlekfon1UERd2LhDAFhAlkOdWS+FqqZ2rNx+FNFhwai30YNBKjm/KwZD/8AeeiTK0m9eq9Pj+U2HPHNCAeLyYYlY9VPPteyqmtoxd71pRVVUWDBulrkXL5EvYUwjd7DWqcEwfYy9aV0sVTQqFRBqpLnynD7GjhXv7apw6Pz9XXyv0B4xcOKQBBTnNEpKM1uNGKJlqt0VdbKNJnRH2UukMpbTwpIvcTa/JueIzACxsaRK6FisdyRyDTbuEAAWkF1J7o54/K7InDf10ONwed+zu7zO5hB6cpxhSpllW8uE39Pwx6iej3ZXYv6kISysktdxdT7vTTGN/Ef3+zauV4jQuk6GkRjm93xtS4fFESSio2/WF53Az0dq0NopfYqxQFHT3A6tTt8jb5k5bhDSz4rE4i2HUddif9YJW40YomUqveD36k2VliKVsUS+QHQdPjmmrifr7I08ZMccIs9i4w4BAGqbOSWbq8hZacrKDLLEW3rocbi8b/ps73FPn4LfuXl0MsalxSMzOVryItsGDa2d7I1IXscd+by3xDTyH5buW3sMIzHqWzstjtBxliNxIZAs++4IPthVYcxbzBvYvrpnLPadaECbUoniY7X4T9EJyY0Yog3JOSkxeHNnud1z9rZKS65HQf6A6/B5D1sjD9kxh8iz2LgTgMwfjtOTuno/kfebNDSBD+Rkkad76OUf4nB5X6TV6fHT77WePg2/ctnQBPx93CBjXu1sT172RiRv4c5pUTwd08h/OLOm3LbDNfhod2WP17k+jnsY8pZbc/ph44GqHo3Kj+amYdoFA3FhvyjcMba/5EYM0Ybk0SkxPltpySm4yddxHT7f4KmOOZw1hKgLG3cCjKWeawrIP3UYucZ7uyowsm8UKzXIIk/10NPq9HiJw+V9iuFB+NM9lWju4LQwctp8sBqFFXV49NLByB2sxrG6FqeOx96I5A08MS0Ke52Ts0TuW1u+KT4l49mQoyytsVPV1I45a4sRFRWGnLMiHGrE0Or0iP5jnbtvik+ZrJ9q3pDM0YREniFlui9W9HuWuzvmcNYQoj+xcSeAWOu5xoYd3yKl8oQPOIHHEz30fv7tNIfL+5D8Ug1e/PYQNM1cZ8dVqs904PG1xVh01XB8Udiz17dU7I1InuapaVHY65yc4ei0mAAQGx6CWoE1Xciznvh8H16YMgyj+8VIKuNYqhSMCQ/BFcMTjdOqdj+etUrLxIhQXDOqDzo6dSgor2NZi0hmotN91TZ34KqVP6H6zJ/5dkLvEGNnK1GsP3GOuzrmuHM0OZEvYONOgHC25xp5D9HKE/ZkIHepamwV2o8V1J7nzPQ0JN2Sbw+jtsX5RjRvm8efAg+nRSFf5Mz9OHl4osUp2ci71LV04IHV+ySVcaw9C9W1dOCj3ZXI7Ge5ItK80rK8rgX/KTqBlduPGvdhWYtIXiLTfU0amoC560t6vG7obCVa0c/6E3m4umOOJ0aTE3k7padPgNzDmZ5r5H3sFVYNhRbz79zQkyG/VOPK06MAkxgZJrQfK6g9S6vT4x9f9Sz4kOvI0evbW+fxp8AiZVoUIm/hyP2YFKnC4rx0jEuLd8EZkasYyjirdhyF1saiSKKVgtaOYai0DAlW4rXtR1nWInIDw8i5RLM8PSlShUVXDcfne4/bfP/T3xywmS8ArD/xJVJGkxO5glanR0F5HTaWVKGgvM5u/uIOHLkTIE42iPWsJ+fEhofg8mEJ+KakCvWtrpvyyFZhlT0ZyN3GDIzz2YVmA8nOo6fRrvX8gwdJkztYjcLKek4LQR4lOi0K83nyJiL3bWJEKJ6aPBS1zR3G6WMAYHd5HaLCgtHgwud5kt/K7UfxZdEJqz3t5ZhikmUtIvezNt3XL8dq7a4f2tyhwy/HanHe2XEWt/M37Vs4mpw8yVtH+HHkTgDIL9Xgn99ySjZ3qG3pwMd7jru0Ycde5Ql7MpC7BSkVeDQ3zeY+XGjW8z60sCAxeS/Dr+Wj3ZW479Mi5K3ayV6D5DGGaVFsYT5PUri616Nh3YRLhyTY3G92bhrGDIjF5cMTkZ0Sg62HNZj87x144LN9bNjxUbZ62stRKciyFpFnGEbOGfLrIKUC3xSfEnqvrf34m3YdV8R6jiYnT/HmEX4cuePnNh2owvyvDnj6NEhG9ipP2JOBPCF3iOWFZpMiVZg1IZXzFHsBVlL5FvOiT/cFQi8dwt8TuZ+1BcWZz5NUru71aOn4CvTMV6PDTIvCr247gvfYEcJrJEWqMGlogsPfiaWe9nJUCrKsReQ9zrRrnd7PU79prU6PPRWmI5H8qZOMtVj/aG4apqkjHT4uR5OTJ3j7CD827vixf20rwwe7uBCot4lWBaG+zfrDRWJEKB4Zn4pl35U5VHnCngzkKdaGy/vTQ6ovG54UgZKqM54+jYB00cA4FJ1okKWB7eWtZRjPtSDIQ5jPk7OsLWbfvQHbmQYea8e31Fe4vrUTj68txqIpwwGADTteJCY8BA+PG4SJQxMwsm9UjwpCEZamV5OjUpBlLSLvkZUcjW1lp4X2s8YTv+kN+0/gyS/3e93UTnKxFevnrC1GVFQYcs6KcOjYhtHklo5vwNHkJDc5pnV1JTbu+KlXtx1hw46XunLEWfhot/XvxhDQJ/yxzoLUyhP2ZCBPMgyXJ+8zLi0BX+wTm7qA5PXryUZ8c+952FtZj3W/nsQ3JdUOH+tUYxv2VNRjcmKUjGdIJI75PDnKkV6PhunVRJ6HRY5vydz1JQgNYiWQN6lr6cDc9SVQKhXGRuXd5XWYveZXtNhZX6M78572clQKsqxF5D1uyErGK9//ZrEB30Dxx37WuPs3nX+oq+HD1ih9TzXwSIm5to5hLxY/va4YX04/F0qFY7GXo8nJ3bx91C4bd/xQe6cO77PnmdcalxaPzH7RdgORo5Un7MlARJY0tnFaNk+pbenAvhMNOHdALEanxKCg3H7PH1s0ZzjVCxH5Hqm9HqVO3yZyfGvatfKu+eNPkiJUuGbUWSitPuP2+eSX5h82NvadOyAWt56bgpXbjwq/31JPe2crBVnWIvIeocFK/DWnn82Rl3/N6YfQYOvLjbvzN63V6fFS/mGbjVFyTO3kSCONXFOmisTiE/Wt2FPh3AgHjiYnd/L2Ubts3PFDn+6ptBksyHMMPT6ClAqXBiL2ZCAic5wexLMMvXiClAo8Mj4Vc9eXOHwsdW9+l0Tke6T0enRk+jaucSK/R8YPwo1ZyQhSKrCxpMrtjTtVTe14a+cx3HX+AADAnWP745PdlagXmObUWk97rU6P6LBgPHjxQNS2dCA2PASJ3cpoIljWIvIeM8cNAgB8UFABXbeKMKUC+Et2P+N2W1zxm7bUwOKOqZ0caaSRc8pU4VgvQ2c1jiYnd/H2UbvWm6/dqL29HVOmTMHOnTuNr5WXl+P2229HZmYmrrzySvz4448m79m+fTumTJmCjIwM3HbbbSgvLzfZ/vbbb+Piiy9GVlYW5s2bh5aWFuO2trY2zJs3Dzk5Objooovw5ptvmrzX3md7u73H6z19CmRF9x4fhkB0+fBEZKfEyN7DIHewGmvvHosV00bhuSuHYcW0UVhz1xgWNsivMZ5Yl5kcjagw9unwlO6Na7G9Qhw+TlKkCln9ONULkTswpshLtJNBXK8Qu1O6PLPhIL4pPoWC8jpo/6jNYycGeSVFqowNO4Dn0ve17UeNjUpBSgXmTRoi9D5LPe3zSzXIW7UT931ahCe/OYhl3x3B8h9+Q31rp+SyGMtaJAXjiWvNHDcIP8y8CI+MH4QbMvvikfFdf4s07BjI+Zvuntcs+PoA7vu0CHmrdmLb4Rqh9zvaWcHQSGNeAW1opLHUQC86ZapWJ9aFXHiEg53OalqdHgXlddhYUmUS64k8wTDCzxZPjtr1eONOW1sbZs2ahdLSUuNrer0eM2bMgFqtxueff46rr74aDz74II4fPw4AOH78OGbMmIGpU6fis88+Q1xcHB544AHo9V0/9o0bN2L58uV45pln8M4772Dv3r148cUXjcdfsmQJ9u/fj3feeQdPPfUUli9fjg0bNgh9ti+ob+HUO97o1px+bn/Yd3UDEpE3YTwRoOdDsSeY9+Jxpnc5p3ohcg/GFPkZej3akhSpgh6w27P5TLsWT35z0Fhhll+qQW1zh4xnS+bxRuT7c5XuFYuGHvbWziUpUmWxl7kjlZ72sKxFIhhP3CM0WIlbsvthzqVpuCXb9lRs1sjxm7aV19hae7k7RxrTHW2kkTKaSIRIrFAqutZWM2do0Hl5axkmr/ipR+OYu0ePEnVn7fnD2nOHO3m0C+/hw4cxe/ZsY4Ay+Omnn1BeXo6PP/4YvXr1QmpqKnbs2IHPP/8cDz30EFavXo2RI0fizjvvBAAsWrQIF154IX7++WeMHTsW7777Lv72t79hwoQJAICnn34a06dPx2OPPQa9Xo/Vq1dj1apVGDFiBEaMGIHS0lJ88MEHmDx5st3P9nb5pRrsqWzw9GmQBZsOVmPGxQP50E/kAown9r3x01E0tGnd/rn+LlIVhGvO6WNzrm/zCjJHCmyc6oXIfRhTXEN0XYMaiVO1GCrnozk6VRbRYcGYN2mIMd50n1ro2lF98JqENW/kYj5NUe5gNcanxeNIYwdKK2tR22x7ejXRSk9n17kgMsd4ElhE8hqloqu/nbUud45O7eTolG9yLxQvEut1euCJdSVYnKcwxhpL08l158gUcURy89a1njw6cscQmD755BOT1/fu3Yv09HT06tXL+Fp2djYKCwuN23NycozbwsPDMWLECBQWFkKr1WLfvn0m2zMzM9HR0YEDBw7gwIED6OzsRFZWlsmx9+7dC51OZ/ezvVl7pw6LNpfa35E8QkpvByKShvHEtle3HcGqHcfc/rmB4M6x/TE0MQL3XjBAuBePSI+2xIhQ/O/153CqFyIPYExxDcNaJzePTkaMWUNM9/yy1kJvXhEi67CQfWHBQRiXGg+g59RCr20/iqiwYI80pJlXLAYpFTg/NR5Xpifhlux+uCI9yWpPe7l7phOJYjwJLCJ5jc5Gww7g+Ch9RxtpXLFQfO5gNRZdNRz2LsMwksjaaCdb7yHyFG8ctevR7k233HKLxderq6uRmJho8lp8fDxOnjxpd3tDQwPa2tpMtgcHByMmJgYnT56EUqlEbGwsQkP/zJjUajXa2tpQV1dn97OlULjx+80/pMELmw6hjoUar6Y50+7W+8KVDNfhL9fjCKaBa9LAkWMxnlj37cFqm6NKyHFKBfDK978Z/07oHYJ7LxiAlNhwqHuHIquf5V48wUEKPJqbhjk2erQ9mpuGsWfHWtzGvMc+ppFtgZI+jl6fP8cUV3znIsfMP6TBS2Y9cmPCQ3DF8ESMS4s3yS+dWZeMnHeqqauRo6G102LP64Y/yptZyVFunTFCHRFqcq9JycdEF+72p7KaqECJB85iPLFM7vvG1+9D0bzmzgvPxvq9x01iYlKkCrMnpCJ3iGOduaQ00nRP51F9o6BUdDU6WaNUdO0n5fuJDQ+xeUygq1F9d0Wd3dFO5u8prKxHTv8Y8ZPxIoGe5/L6Tf8rF68cu97S0mISiAAgNDQU7e3tdre3trYa/7a0Xa/XW9wGdC1yZ++zpYiPj5T8Hkds2H8Cj68tttn6T46xF+SkqmnTQa12z33hLu66z70Z08B70yDQ44lWp8eS/B0OvZfsM48PmjMdWLn9KP7919GYPLKPzfdOU0ciKioMT68rxon6VuPrfaLD8NRV6XbfD3jv786bMI1sY/pI4w8xxRXfub1nW2tllfqWDny8uxLj0pOQlBhlfH1wsuPrkpE8WhRKLNt2xOp2BYCjtS1Wt8utT3QYLsvsZ7HDhMg9ndpX7J5K7Rvjd2U1UYwH7uUP8QSQ/77x9d+faF5zWfpZmP8/6fj5t9OoamxFYmQYxgyMc2oEwGVxEeiz8RBO1rdarBtUADjLQl66o6zGbp2XTg/81tiBCyXMItBWIdb4X6xpERqxY3JspRJqdSS0Or2saehOgZ7nBvr1x8XJe/1e2bijUqlQV1dn8lp7ezvCwsKM280DT3t7O6KioqBSqYx/m28PDw+HVqu1uA0AwsLC7H62FDU1jS5fu1qr0+PJL/ezYUdmUWHB+OdVw9HQ2okn1pXIdtwPdx7FTaOSfCbg2KJQdGXI7rjPvRXTwDVpYDimHAI9nuw6VofTZ7jAtDNG9onA7zUtaGr/c70iaw3/hpeeWvMrshJ7283rc86KwJfTz8WeinpozrSbjPbRaBqtvo95j31MI9sCJX3kjCeAf8QUV3zntvIrW2UV8zwTAAqO1eHn8lqogpVo69TJe6Ik7NipBpOOB+b0AE43d6BXiBLNHa7/nh4ZNwi1p5tMXpOSjw2KDEFiRKjNCsSkSBUGRYbYvJ/9UaDEA2cxnlgm933j678/0bxmzMA41NU2YXB0KAZHdzW0medxjnhk3CCrMwPoYTkvLTteJ3Ts+z8owIJJQ4RHFql0YrGhuaVNaD/zY3+6/bceI4ITI0LxaG6aw6Of3CHQ81xef9f1nz7dKGsDj0fX3LEmKSkJGo3G5DWNRmMcOmpte0JCAmJiYqBSqUy2d3Z2oq6uDgkJCUhKSkJtbS06O/+cvqy6uhphYWGIioqy+9lS6PWu/7enwv6cniTd/ElDcG7/WFw6JAGL89KR0Fue6SFONbZhT0W9W+4Nd/wDPH8Onv7HNHBNGsgl0ONJVaP0h2XqkhgRiltz+qGqsd2kYad3iFJoigHRvF6p+GPO3mFdc/YqFQrmPV6cN/nTv0BJHzn5Q0xxRbrZOo5IWeVUYxve+OkYLvu/HXjgs314e2cFG3Y8KClShdhwsbLPVSPPcum5KBXAoinDMWGw2ql8TKnoWuDbllkTUoVjsL/9E03HQP8nJ3+IJ4D86ebp79jZfyJ5zew/1tRxxedPGKzG4rx0q+uAWspL1b3FpnNraO3EnLXF2HJII3QuImuMJkWqkNMvRujzu7+ntqUDcyys0VPV1C7pHD31D/D8OfD6PX/9cvLKxp2MjAz8+uuvxuGmAFBQUICMjAzj9oKCAuO2lpYWFBcXIyMjA0qlEuecc47J9sLCQgQHB2PYsGEYPnw4goODTRaLKygowDnnnAOlUmn3s73N/2fvzuOiqP8/gL+WGwUBQUiBPFA8ERDUDk3la2qmZmqWlkdZanlUmilq3kfe5tFhHt15VD+vDlMxsyzzAjJFES9ERBblUg5h5/cH7cYCuzu7O3u/no8Hj3Lnszuf+ezsvOczn4sP7qTl5+FabfHruGYB2DP6Ibzy8IOS7EPsQndEZDxHjyeGLkrt6CLqe+PNbmH4/MT1apWGuyJ7KPNaT2R/HD2mGELstXDD0auqtVzIsiZ1C0Ogt7uotPvO3YKnq+keKSzs0xLdm9eT5LPidDz0jNNjuiEiYzGe2C+d1xoTjyqJaxaA3a90xIeD22JB7xb4cHBb7Hq5g8ZrXET9ijV3xFp5KA3lItYucHbS3NCl3N2kbmFoF+qrsxGosje6NMGqQ2mS5JHIXlhl406HDh1Qv359xMfHIzU1FRs2bEBycjIGDRoEABg4cCBOnTqFDRs2IDU1FfHx8QgJCUHHjh0BVCxat2nTJhw4cADJycmYM2cOBg8eDE9PT3h6eqJ///6YM2cOkpOTceDAAWzevBnDhw8XtW9rcuB8NpbqsfAY6Tb/yeY1Bj1np4qe1VIQu9AdERnP0eOJ2J639J9WQV74+LkonZUGXXitJ7I/jh5TDGGua2FtN2ez7MeeVW7kENPjGgByi8tQZIJp2ZR56R4uTcOOkr4PPYlMhfHEvln6WqN8ftWzZcXMANqmiv47M1+vdaazCkqQmJEnKq2mhq4HfDyw9N94o60RqDJlXPCr5SpqRLDYPBLZA6tcc8fZ2Rnvv/8+ZsyYgQEDBqBhw4ZYv349GjRoAAAICQnB2rVrsWjRIqxfvx7R0dFYv349ZLKKC9aTTz6JjIwMzJo1C6WlpejRowemTJmi+vz4+HjMmTMHI0aMgJeXFyZMmIAePXqI2re1WHP4Ej4/cd3S2bA7uUWaewxK0Qs7yNsdUcE+Rn8OEYnj6PHEX+QwewI8XJ0w4/Fm6NUyCCfTc42a8tTP05XXeiI75OgxxRDKRgJTTyPdv+0D2J+SzemqDfRm1yZ4NjpY9QBQ+bBtqoa1G6QW6OWG2b2a4869+wjwckNUsI/J1iiVstMekaEYT+yfrVxrDHnOpc974poFoEuYPxIz8iAvLEWAlxsejwrBnduFqqmplI1AK6qsoePn6YpeLQPRpam/Ki7sO3dL8jwS2TqZIEg90xspyeWmWSDqwIVsxO85J/0HEz4c3FZjAD6Znoux25ON+nx7GvIvkwEBAd4mO89tAcvANGWg/Ez6j6Hle/zqHbz2zd/SZ8gOvPLwg4gO9sHtGh4k7Tt3CzN/SDH4s4e0C8akbmFSZbUaXnt0Yxlp5yjlw3hSndjvvP2KX0V/5vHJj2ndnpAqN3kjQZC3O97o0gTxe1lHMsSC3i3Qs2X19TYSUuVYvD8VuSae5tWQOpKjXMdMjeUoDuNJzcScN1LGE3tgbb85Q55zaXtupotMBvjV9cL+xOuqxh5lPaxcIag1AtXU0C82v8bk0ZSs7fs3Nx5/xfHn5BTA31+6mGKVI3eoZuUKAafSczHbiAdOpJmuUTXG9Dx0kgELn2xpNw07RGQb5HfZY0mT3WeyMOqhhmoVBmWF4vLtu0Z9dpem/sZmj4jIbmjqkRvk7Y7+EQ/go6NXjd5HVkEJ/Gq5YswjDSX5PEejafq8uGYBKLlfjlk/njfJfoO83DEpLox1JCKyWmIaHGyZvs+5jJ2NJuGCHKsO/4XMvP/WfAr0csPkuKaIaxags0FGTH45Yw45Gjbu2IiEVHm1ChFJa1K3MK1B2pjpCRQC4FeLa18QkXndMXFPW1umnItZWYGQKs6yMkFEVF1N07Ior5XfJd1A9l3j49Xhizl4vUsTfHXyOgpKyo3+PEehK24FerubZL+jH2mIlzo+aNRD0nKFgBPXcu32oSsRWVZN9YPKDRH2QN/nXLqem2mjaSTvrcJSTN19VtQoTjH5NSaPRLbIydIZIN2UF0A27JhG5cVDdVH2PKzjoX+7KOf8JCJz83ZnHw5tlNdlKeMsKxNERDWraYFnZycZ3vpfM0k+/+tTGTicloMhMSGSfB4AjHooVLLPsla64payl7RUlHWvVx5uaFS8TLggR6clCRi7PRkzf0jB2O3J6PfxMSSkyiXLKxE5Lk31A2VDhD1da5TPubRd6/V5blaTcoWAFQkXtaZZeSgN5Qrdc3Vpyq+xeSSyVXzqY+XEXABJf93DA9C1aYDBPbzyi8v03qem6Q6IiEzl7M0CS2fBqgV4uUkaZ8c80pCVCSIiPSkf0iz8+YJB99iVrTyUhu9eao9tpzKQZ+RnAYCTTIbabs64W2qbI4GCvN1Va8DVNC3epG66p0QzZvYCP09XvP2/pvCr5Srp6Bopen8TEWkitiGiS5i/3XTqqjrC1q+WK2RAjeuTGiIxI09nR7qqMyvok1+O3iRHxsYdKyfmAkj6GxTVwKDF1Qx9CMhpeoiIpNPQzx1X75QY9RnK67KUcTbU11OSzyEicjTKhzSn0nNxIj0XMllFw8rO5Ey9pmzLKijB35n5mN4j3KDGiKo+/uOa0Z9hCaMeCkX7B/3UHnQZ8xBM07pJ2vh5umLv6I5wc5F2shBHfOhKROYlRUOELa7VoxxhawpiZ7LRZ8YbU+aXyJawccfKcSov0zC0XA19CMhpeojIEoJ9PSydBZOo5eoKwLjGHeV1Wco4yxGaRESGc3aSoX1DP7Rv6Kd6bdRDDbHh6BVsPpYu+nPkhaXo2TJQ78YIaxXk7Y43ujbBykNpyBZ5LI3r1q72wMvYh2BVe0mn5xbho6NXNaaf9ngzyRt2AOl7fxMRVWVsQ4S2tXr+F+6YowrF1pNYnyLSHxt3rFzdWq6WzoJdEhswqva2uFWg38NEsdMdEBFJLSFVjq9OZlg6GybhLXLdsyHtgnHwQrbWaWjExgNfDxfkapnihyM0iYik5+wkQ4eGfno17iiv68rGiE1/XrXpETivPNwIzk4yOMlkokcjmerhWNUGoiYBtQ2e7q0qsb3cTdH7m4ioMmMaInRNG7m0XysMDvA2Oo+2Rrl+m7bGedaniAzDxh0rpmztdyQ+Hi6SzI+tjdiAUVNvC19PcY1tNU2FQERkLpoqFfbi+dhg/HUtV2e6Lk398XqXJlofFkUF+6COh4vWdR58PFww9fFmiN9zTmMajtAkInviKgPu617TGK5muOyJeSCkVPU+/3BaDnb9fdNkeXusiR+ebReCo5dv40sTdKho/6CfKrbENQvA4j4tMX3vOWj7asz5cEyqNQ+09XKv2kjE3t9EZGqGNkSImTZyxaE0DHyokRTZtCmV12+TATXGMdaniAwj/ThpkoTywZytTyMgVpC3O5b0a4V9rz6M9YMiUMfdWed7no8JRmCVm3Y/T1d0alxX6/vEBAxN5Z9bpHvO7yBvd7zycCPEhPoyMBGR2Rm6NpitaBnkhY4N61a7/lelrHApexn3bBmo8bos5krdrWnFegNV96uMXxyhSUT2ROQASdHpjKF8ICRG5ft8XfWpoe2Cjc5bdIgvOjT0wxtdwzAsNkRUPBGrpgeH3ZvXw6K+LbW+z9wPx8TEWW00fU/KXu4JqXK115UPXbVh728iMoaYuFPTtVbstJF/Xb5tdB5tUVyzACzt1woP+KhPHc76FJFxOHLHCtn7gzmgohf0c+2CEerrWa2Hl7OTDPkl5To/o3OYPyY8VnOP7Jp6f4mdIsDY8mdvAyKyJEPXBrMVt+9VNLIre35pIvZanJiRp3PEaF5xGRIz8iTroUxEZO2Kdd+K65XOWHHNArSuoVP1Pl/M/fzW0zWPtKlX2xV5RfdRqtCdr8qjPid2aYKxjzbC4gOp2PtPlu4366ApjnUPrwenfjLJpkOzJDHf08pDaegS5q9WV2TvbyLboel3WlM6a6Ip7mi71oqdDvJWQTGa+Tjm6MK48AAMfKgR9ideZ32KSCJs3LFC9vBgbswjDWucg7nOv406L3V8UO3iXa4QcDI9F/LCUly+fVfUPuSFpRoXBjXmAZzY8q9b2xW37/43kscWK1REZH+sdY55JxmgEFOz00G5SLIhFa6a6Dt3v7ELUhMR2YJyEQ0b+qSTQuX7+1sFJbhTdB9+nq4IrDRSU0nM/bymmNS/bX3Ra/TIqlQtnJ1k6NM6CN7uLvjxXBZyi7R3HnBxAurWctM7jtlLZwOxvdwTM/LUYq+y9/eqw5eQmVesep31MSLrI/b2X4Jqgihi1/cC9L/Wip0OMtDbQ3ciO+bsJEPsg74QzPWlE9k5Nu5YEWWQOXhBrjuxlQv19RQdCGsaZSOGrsBp6AM4sQ/63unTGp6CwqYrVERkf6x1jvnHwwOw77w08U15nZbi4Rbn7iciqk7sVdTcd75i7++N6eiw/fQN0WljK+WlpjpNbVcn3L2vuQVsYZ9WBscxe+hsoG8Hi8rY+5uI9KXP+l5K+lxrxa7V06FxXdy5XahX3omINGHjjpUwtIHDWikfgukKhIYu+m3KeZTFPsB7oI4Hmvm4sbcBEVmVO/fuSzZKRkp92jyAP6/m6pwCTYzK12ljH24ZumAqEZE9c3UGykVMueaqe5lMizCmQV5snKrt5ox2/8YfTXUaZcOOl6sMhff/C8wBtVwwpXu46mGirTfSGMrYDhbs/U1EYmm6TivX95JizZfK00ZqMpnTRhKRxJwsnQHSvdinOdVydcKjjf2M+ozKD8GU063tO3cLJ9NzUV7paaMxa9uYch5lsYt0dmhc1yT7JyIyVEKqHPF7z1ldww4AtAvxxfQe4UZ/jtQNLYYumEpEZM/cXMS12ohNZ25i7ue1qeOu+7hm9giHs5NMVJ2mtrsb3h8UgQVPtsDXrzyE78c+bNBDRG11K1sktt7FDhZEtkvE5VSvdIYQu76XFNdU5dTRVa9tQd7uFQ1I4Zw2koikxZE7FmZMA4cpvNOrOW4VlOD3y3cM/gzlQzBdQ14NWVvIHPMos7cFEdkia4snVf2dmY+4ZgEY/UhDbDh61eDPMUVDi1Tr9xAR2Qv/Wq7IL9E9dMe/lqsZcqM/Mffz2jwXE6I1Vg2LDUH35vUAiFw3prAETk4y9GoZiIAAb8jlBXqPNjFkOiFrJ+Z7YgcLItvm5+GKm5XWKtaWzlQMXd/LUPayLhoR2QY27liYvg0cPh4ukkxpU1W9Wq7o1SoIqw6lGTyCqPJDMDFDXu+XiVuB9aWOoWjiX9usAVHngz72tiAiK2Nog3n35gH48kSGiXL1H+V8+S91fBA7kzN15lUG9YVVTd3QwkoYEdF/IhrUweU7xaLSWStN9/O6pi4N8nbHSx0fRFhA7Wrv9fN0xdvdm6J7eD3Va8asGyOWOaYTshR2sCCyb+0b+WLPP9mi0pmKOa7TVdnDumhEZBvYuGNh+gQPXw8XPBPdAB//cU3SPPRpHYRHG9dF/N5zBr3/2egG6NYsQPUQTOyQ11k9xU3P06Ghn0WCIh/0EZEt0bcy4uvhgje6NsGVnHsmypG6ymux6eql+2b3cDzTJhDJN/LNev1lJYyIqEJJubhOWGLTWUpN9/NHLuVo7dTQo3k9ODvJRNcFjF03RhexdasuYf42W09hvYvIfpWUiRumKDadIUx9nSYisiQ27liYPsEjt7hM8oYdAOjwoC9W/ZKm9/s09aYSO+RVBlj9ItZ80EdEtkLfykhucRni95yDp6vpl9+rei3X1kt3crcwDH6kMeTyAl5/iYgspPi+uIdsYtNZUuX7+XKFgFk/pGhN//P5bIzr3BjOTjJRdQHlujGmqtOYezohS2G9i8g+ZRXoHgWqTzpDmPo6TURkSWzcsTAxQcbU7hTdF7X/Nx5rjGaBXrhTdB9hDXzRxNsVTrLqvanE9h6/fe8+51gmIpKIofGk6L7pe13XdC3X1EvXxZnXfCIiS4uo74XDaTmi0tkSUzSUmHrdGEtMJ0REJBUXkZc+sekMwfW9iMiemb67LmmlDDKWEuTtDj9PcQvXBXi5o0NDP/RqGYiHtQz712fIq7L3dmCV9wR5u9v03NFEROZm6XhSE13XcmUv3Z4tAxET6ssKFRGRlXASeT0Wm85amKqhxJR1Gk4nRES2zMlJ3GNHsekMxWdPRGSvOHLHCmiansYcJnULg4+HuNNAbIVB3yGvnGOZiEgalownlQ1pF4wuTf15LScislGZ+eJiiNh01sKUDSWmqtNwOiEismW13MQ9bxKbzhh89kRE9oiNO1ZCGWS2nc7Aql8u6Uw/+pGG2JmcafDDu8rr5ZQrBEkrDIYMeeUcy0RE0qhcaTl+7Q42/Zlutn1rWouNiIhsS4ivh6TprIWpG0pMUafhdEJEZMuig31wOO22qHTmwGdPRGRvOC2bFXF2kuHZ6OBqw0SrCvJ2x0sdH8TuVzriw8FtsaB3C7w/KELn+/w8XTGnVzje7NoE4zo1go+HC8oVgqipfPStMHDIKxGR5SgrLa883EhnbBA7elMTTbGFiIhs16DIBtB16+8kq0hnS0xR7zEH1q2IyFY9Ex0MXVdU2b/piIhIfxy5Y2X07ZlVuceBrve1bVAH7/92Ra2nWqCXGybHNdU4lY8xvbA55JWIyLLExJTpPcIBoNr138/TFb1aBqKOhws+OnpV4/t1xRYiIrI9bi5OeD4mBJ+fuK4xzfMxIXBzsb2+gqao95gD61ZEZIvcXJzwQqz2ePJCrG3GEyIia8DGHStkaIUjrlkAhmkJmofTcqq9dquwFFN3n1X1+JK6wsAhr0REliU2pmi7/t8rLTcqthAREVkTW20oYd2KiIiIiCpj446VMqTCUa4QsC/llkH7W3koDV3C/FlhICKyQ2Jiiqbrv1SxhYiIbEdpmQJfntTcyxoAvjx5HWMfbWSzva1Z7yEiMj1HiCdERJbEK6cGJSUlmD59OmJjY9GpUyds3rzZ7HlQVjh6tgxETKivzodjiRl5WhcH1SaroASJGXkGvZeIiDSzhngC6B9TlBhbiIish7liyjdJN6Br+TSFUJGOiIhsD+MJEZF94MgdDZYuXYozZ87g008/xY0bNzB16lQ0aNAAvXr1snTWNJIb+PBNqvcTEVF1thhPKmNsISKyHuaKKddziyVNR0RE1oXxhIjIPrBxpwb37t3Djh078PHHH6N169Zo3bo1UlNT8eWXX1r1w7gALzeLvp+IiNTZajypjLGFiMg6mDOmhPh6SJqOiIisB+MJEZH94LRsNUhJSUFZWRmio6NVr8XExCApKQkKhcKCOdMuKtgHgQY+RAvydkdUsI/EOSIicmy2Gk8qY2whIrIO5owpgyIbQNfsnU6yinRERGRbGE+IiOwHR+7UIDs7G35+fnBz++9hVkBAAEpKSpCbm4u6deuK+hyZmdePdnGW4a24pnh791m93zu5WxhcnMVlWHlc5j4+a8IyYBkALAPANGVgT+Vpq/GkMnPFFiX+rnRjGenGMtLOUcrH3o5PipgitkzcXZ3wfEwIPj+heRHs52NC4O7KvoL6cJTfnjmwLKXBchTH3srHnHUUxhN1jv6b4/Gr/9fR8PjV/ysVNu7UoKioSC3IAVD9u7RU/NoB/v7ekuZLjMEB3qhTxwNz95xFZt5/c5bW9/FAv8j62J2UWe312X1boVeb+nrvyxLHZ21YBiwDgGUAsAw0seV4Upk5Y4uSpY/ZFrCMdGMZacfysS1SxBR9vvP5gyJRq5YrPj5yWW0xbCcZ8Ernxojv3Ur0Z5E6/vakw7KUBsvRsZi7jsJ4Up2j/+Z4/Dx+R1a3rrTHz8adGri7u1cLaMp/e3iInwc0J6cAgqA7ndRiH/DCzlHtcfp6HuR3SxFQ2w3RIT5wdpLhpdiQGl+XywtEf75MVvFDtNTxWQOWAcsAYBkApikD5WfaA1uPJ5WZOrYo8XelG8tIN5aRdo5SPvYUTwBpYoq+3/krHUIxol0wvkm6AXlxOQI8nDEosgHcXJwMusY7Okf57ZkDy1IaLEdxGE9qps95w3hSwdF/czx+Hj+P3xu3bxdI2sDDxp0aBAUF4c6dOygrK4OLS0URZWdnw8PDA3Xq1BH9OYIAi52sTjIZYkJ9q+VH0+uGsOTxWQuWAcsAYBkALANN7CGeVGaO2FL5/dZwzNaMZaQby0g7lo9tkSKmGPKduzo7YWhMCAICvCGXF/C8kQDLUDosS2mwHB2LpeoojCf/ceRjB3j8PH4ev5QcY1JLPbVs2RIuLi5ITExUvXby5ElERETAyYlFRkRE4jCeEBGRVBhTiIhICownRET2g1ftGnh6eqJ///6YM2cOkpOTceDAAWzevBnDhw+3dNaIiMiGMJ4QEZFUGFOIiEgKjCdERPaD07JpEB8fjzlz5mDEiBHw8vLChAkT0KNHD0tni4iIbAzjCRERSYUxhYiIpMB4QkRkH2SC4Miz3JmWcg5ReyOTQW2OVEfEMmAZACwDwDRloPxM+o8jnWP8XenGMtKNZaSdo5QP40l1hn7njnLOmBrLUTosS2mwHMVhPKmZIeeNo59zPH4eP4+fx5+TUwB/f+liCkfumJBMZukcmIbyuOz1+MRgGbAMAJYBYJoycOTy1MSRyoS/K91YRrqxjLRzlPKx9+MzhKFl4ijnjKmxHKXDspQGy1Eclk/NDCkXRz/nePzq/3U0PH71/zoaUx0/R+4QERERERERERERERHZECdLZ4CIiIiIiIiIiIiIiIjEY+MOERERERERERERERGRDWHjDhERERERERERERERkQ1h4w4REREREREREREREZENYeMOERERERERERERERGRDWHjDhERERERERERERERkQ1h4w4REREREREREREREZENYeMOERERERERERERERGRDWHjDhERERERERERERERkQ1h4w7VqLS0FH369MGxY8dUr6Wnp2PkyJGIiopC79698dtvv6m95+jRo+jTpw8iIyMxfPhwpKenmzvbksjKysLEiRPRoUMHdO7cGYsXL0ZJSQkAxymDq1evYtSoUYiOjkbXrl2xceNG1TZHKYPKRo8ejWnTpqn+ffbsWTzzzDOIjIzEwIEDcebMGbX0e/fuRffu3REZGYlx48bh9u3b5s6yJPbv34/mzZur/U2cOBGA45QBmYYjxxhdGIN0Y4wSz1HjF0mrpKQE06dPR2xsLDp16oTNmzdbOks2wZj7KKrA+wVp1FSOCxYsqHZ+fvHFF6rtjAdkCo4WT4y5r7c3+t6T2oPS0lLMnTsX7du3xyOPPIKVK1dCEAQAjnH8mZmZGDNmDNq1a4e4uDh88sknqm32fPyWuHdh4w5VU1JSgkmTJiE1NVX1miAIGDduHAICAvDtt9/iqaeewvjx43Hjxg0AwI0bNzBu3DgMGDAA33zzDerWrYvXXntNdeGyFYIgYOLEiSgqKsKXX36JVatW4dChQ1i9erXDlIFCocDo0aPh5+eH//u//8PcuXPxwQcfYM+ePQ5TBpV9//33OHz4sOrf9+7dw+jRoxEbG4vvvvsO0dHRGDNmDO7duwcASE5OxowZMzB+/Hhs27YN+fn5iI+Pt1T2jXLx4kV069YNv/32m+pvwYIFDlUGJD1HjjG6MAbpxhglniPHL5LW0qVLcebMGXz66aeYPXs21q1bh59++snS2bJ6ht5HUQXeL0ijpnIEgLS0NEyePFnt/Bw4cCAAxgMyHUeKJ8bc19sbfe9J7cWCBQtw9OhRbNq0CStWrMD27duxbds2hzn+N954A7Vq1cJ3332H6dOnY/Xq1di/f79dH7/F7l0EokpSU1OFfv36CX379hXCw8OFP//8UxAEQTh69KgQFRUl3L17V5V2xIgRwpo1awRBEITVq1cLL7zwgmrbvXv3hOjoaNX7bcXFixeF8PBwITs7W/Xanj17hE6dOjlMGWRlZQmvv/66UFBQoHpt3LhxwuzZsx2mDJTu3LkjPPbYY8LAgQOFqVOnCoIgCDt27BDi4uIEhUIhCIIgKBQK4fHHHxe+/fZbQRAEYcqUKaq0giAIN27cEJo3by5cu3bN/AdgpMmTJwsrVqyo9rojlQFJy9FjjC6MQboxRonj6PGLpHP37l0hIiJC7Xeyfv16td8S1czQ+yji/YJUNJWjIAhC586dhSNHjtT4PsYDMgVHiyfG3NfbE0PuSe3BnTt3hFatWgnHjh1TvfbRRx8J06ZNc4jjz83NFcLDw4Xz58+rXhs/frwwd+5cuz1+S967cOQOqfnrr7/QsWNHbNu2Te31pKQktGrVCrVq1VK9FhMTg8TERNX22NhY1TZPT0+0bt1atd1W1KtXDxs3bkRAQIDa64WFhQ5TBoGBgVi9ejW8vLwgCAJOnjyJ48ePo0OHDg5TBkpLlizBU089haZNm6peS0pKQkxMDGQyGQBAJpOhXbt2Gsugfv36aNCgAZKSksyadymkpaWhUaNG1V53pDIgaTl6jNGFMUg3xihxHD1+kXRSUlJQVlaG6Oho1WsxMTFISkqCQqGwYM6sn6H3UcT7BaloKsfCwkJkZWXVeH4CjAdkGo4WT4y5r7cnhtyT2oOTJ0/Cy8sLHTp0UL02evRoLF682CGO38PDA56envjuu+9w//59XLp0CadOnULLli3t9vgtee/Cxh1SM3ToUEyfPh2enp5qr2dnZyMwMFDtNX9/f9y8eVPUdltRp04ddO7cWfVvhUKBL774Ag899JDDlEFlcXFxGDp0KKKjo9GzZ0+HKoM//vgDJ06cwGuvvab2uq5jvHXrll2UgSAIuHz5Mn777Tf07NkT3bt3x/Lly1FaWuowZUDSc/QYowtjkH4cOUZp4+jxi6SVnZ0NPz8/uLm5qV4LCAhASUkJcnNzLZcxK2fMfRTxfkEqmsoxLS0NMpkMH374IR577DH069cP//d//6faznhApuBo8cSY+3p7Yeg9qT1IT09HcHAwdu7ciV69euF///sf1q9fD4VC4RDH7+7ujlmzZmHbtm2IjIzEE088gcceewzPPPOM3R6/Je9dXAzMMzmYoqIitSAMAG5ubigtLRW13VYtW7YMZ8+exTfffINPPvnE4cpgzZo1kMvlmDNnDhYvXuww50FJSQlmz56NWbNmwcPDQ22brmMsLi62izK4ceOG6lhXr16N69evY8GCBSguLnaYMiDzcZRri74cPQbp4qgxShvGL5KapvMGAM8NLYy5jyLNeJ2XxqVLlyCTydCkSRO88MILOH78ON555x14eXnh8ccfZzwgk3D0eKLPfb09MOae1B7cu3cPV69exdatW7F48WJkZ2dj1qxZ8PT0dIjjByo6EnTr1g0vvvgiUlNTMX/+fDz88MMOc/xK5rh3YeMOieLu7l6tN0VpaanqIu3u7l7txCstLUWdOnXMlUXJLVu2DJ9++ilWrVqF8PBwhyyDiIgIABWB+a233sLAgQNRVFSklsYey2DdunVo06aNWk8bJU3HqKsMqrbeW7vg4GAcO3YMPj4+kMlkaNmyJRQKBaZMmYIOHTo4RBmQ+Tji9VUXxiDdHDVGacP4RVLTdF4AqPawhv5jzH0UacZYKI3+/fujW7du8PX1BQC0aNECV65cwddff43HH3+c8YBMwpHjib739fbAmHtSe+Di4oLCwkKsWLECwcHBACo6fnz99ddo2LCh3R//H3/8gW+++QaHDx+Gh4cHIiIikJWVhQ8++AChoaF2f/yVmePehdOykShBQUGQy+Vqr8nlctXQMU3b69WrZ7Y8Smn+/PnYsmULli1bhp49ewJwnDKQy+U4cOCA2mtNmzbF/fv3Ua9ePYcog++//x4HDhxAdHQ0oqOjsWfPHuzZswfR0dEOcx4AgK+vr2oeVAAICwtDSUmJw5wHZD6O9LsSw5FjkC6MUdoxfpHUgoKCcOfOHZSVlaley87OhoeHBx+Y62DofRRpxuuYNGQymaphR6lJkybIysoCwHIk03DUeGLIfb09MOae1B7Uq1cP7u7uqoYdAGjcuDEyMzMd4vjPnDmDhg0bqjXYtGrVCjdu3HCI46/MHPcubNwhUSIjI/HPP/+guLhY9drJkycRGRmp2n7y5EnVtqKiIpw9e1a13ZasW7cOW7duxcqVK/Hkk0+qXneUMrh+/TrGjx+vurkHKi7MdevWRUxMjEOUweeff449e/Zg586d2LlzJ+Li4hAXF4edO3ciMjISp0+fhiAIACrmVD916pTGMsjMzERmZqbNlcGRI0fQsWNHtV7w586dg6+vL2JiYhyiDMh8HOX6KoajxyBdGKO0Y/wiqbVs2RIuLi5qi7qePHkSERERcHJiVVITY+6jSDPGQmm89957GDlypNprKSkpaNKkCQDGAzINR4wnht7X2wNj7kntQWRkJEpKSnD58mXVa5cuXUJwcLBDHH9gYCCuXr2qNiLl0qVLCAkJcYjjr8wc9y72eQUlyXXo0AH169dHfHw8UlNTsWHDBiQnJ2PQoEEAgIEDB+LUqVPYsGEDUlNTER8fj5CQEHTs2NHCOddPWloa3n//fbzyyiuIiYlBdna26s9RyiAiIgKtW7fG9OnTcfHiRRw+fBjLli3D2LFjHaYMgoOD0bBhQ9Vf7dq1Ubt2bTRs2BC9evVCfn4+Fi5ciIsXL2LhwoUoKirCE088AQAYMmQIdu3ahR07diAlJQVvv/02unbtitDQUAsflX6io6Ph7u6OmTNn4tKlSzh8+DCWLl2Kl19+2WHKgMzHUa4tujAG6cYYpR3jF0nN09MT/fv3x5w5c5CcnIwDBw5g8+bNGD58uKWzZtWMuY8izXidl0a3bt1w/PhxbNq0CdeuXcNXX32FnTt34qWXXgLAeECm4WjxxJj7entgzD2pPWjSpAm6du2K+Ph4pKSk4MiRI9iwYQOGDBniEMcfFxcHV1dXzJw5E5cvX0ZCQgI+/PBDDBs2zCGOvzKz3LsIRBqEh4cLf/75p+rfV65cEZ5//nmhTZs2wpNPPin8/vvvaul/+eUXoUePHkLbtm2FESNGCNeuXTN3lo320UcfCeHh4TX+CYJjlIEgCMLNmzeFcePGCe3atRMeffRR4YMPPhAUCoUgCI5TBpVNnTpVmDp1qurfSUlJQv/+/YWIiAhh0KBBwj///KOW/ttvvxW6dOkiREVFCePGjRNu375t7ixL4sKFC8LIkSOFqKgo4dFHHxXWrl2rOg8cpQzIdBwxxujCGCQOY5R4jhq/SFr37t0T3n77bSEqKkro1KmTsGXLFktnySYYcx9F/+H9gjSqluP+/fuFvn37ChEREUKvXr2Effv2qaVnPCBTcKR4Yux9vb3R957UHuTn5wtTpkwRoqKihIcfftjh7gNSU1OFkSNHCu3atRO6d+8ubNmyxWGO39z3LjJB+HccFBEREREREREREREREVk9TstGRERERERERERERERkQ9i4Q0REREREREREREREZEPYuENERERERERERERERGRD2LhDRERERERERERERERkQ9i4Q0REREREREREREREZEPYuENERERERERERERERGRD2LhDRERERERERERERERkQ9i4Q0REREREREREREREZEPYuEM279atW3jnnXfQqVMntG3bFk8++SQ2bdqEsrIyAMB3332HuLg4yfZ37NgxNG/eXK/3xMXF4bvvvgMADBs2DGvXrjUqD5U/Tx/l5eVo164ddu7cqfb6rFmz0Lx5cxw7dkzt9ZEjR2LhwoU6P9fYY9q2bRseeughREdH48svv9S7fA0hxfdARGRqpaWl6NOnj9r1WS6XIz4+Hg8//DAiIiLQp08ffP7552rvO3fuHE6dOmX0/qdNm4Zp06bVuO327dt44YUXEBERgalTp5rlumpIDCYicnRZWVmYOHEiOnTogM6dO2Px4sUoKSkBwJjCmEJEtubevXtYvXo1evXqhbZt26Jjx46YOHEiUlNTDf7Mmp4H2ZrKz/6qXt+limMAUFhYqPZMbdq0aWjevHmNf2VlZVi7di2GDRsmyb61sYfvkAzDxh2yaZmZmXjmmWdw/fp1rF69Gt9//z3GjRuHL7/8Eq+++ioUCoXk+4yOjsZvv/1m8PvXrl2Ll156ScIciefs7Izo6GgkJyervX7s2DEEBgaqBQKFQoHk5GR07NjR5PlatmwZhg4dir1796JJkyYm3x8RkS0oKSnBpEmT1CpqgiBg9OjRuHv3LjZu3IgffvgBo0ePxurVq7F582ZVunHjxuHKlSsmzd/u3btx5coV7Ny5E1OnTjXpvoiIyDCCIGDixIkoKirCl19+iVWrVuHQoUNYvXo1YwoRkY25e/cuhgwZgu+//x5TpkzBjz/+iE2bNqF27dp47rnnkJ6ebtDn/vbbb4iOjpY4t5ZT9bmdlHHsk08+wbfffqv22hNPPIHffvut2p+Li4sk+yTShmcZ2bT58+cjNDQUGzduhLOzMwAgNDQUUVFRePLJJ/H111/D09NT0n26ubmhXr16Br/f19dXuswYIDY2FgcPHlT9OysrCxkZGZg4cSIOHz6sev3ChQu4d+8eYmJiTJ6ngoICdOjQAcHBwbh+/brJ90dEZO0uXryIyZMnQxAEtdfPnz+Pf/75B5988gnq1KkDoCLuXb9+Hdu3bzdr54HCwkI0atQIYWFhZtsnERHp59KlS0hMTMTvv/+OgIAAAMDEiROxZMkSPPXUU4wpREQ2ZP369cjJycEPP/ygum4HBwdj8eLFyMzMxCeffIJ33nlH78815hmXNTL2uZ02VetnAODh4WF3ZUi2gyN3yGbJ5XIkJCTglVdeUTXsKDVo0AADBgzA9u3bVa+tXLkS7dq1Q+fOnatNNbB161bExcUhOjoaw4YNw/nz51Xb4uLisGzZMnTq1An9+/fHn3/+qRreef36dTRv3hzr169H+/btMW/ePNXnde3aFe3atcP777+vtq/KUwzcuHEDL730EqKjo/Hwww9j/vz5uH//PgCgrKwMK1euRKdOnRATE4OJEyfizp07qs9JTU3Fc889h4iICPTv3x/nzp1TbcvMzMTYsWMRGRmJuLg4rFu3DuXl5QCA9u3bIyUlBaWlpQCAP//8E23atEHXrl2RlJSEoqIiAEBSUhKaNWsGPz8/AMChQ4fw9NNPo23btujduzd+/vlntePKysrCyy+/jIiICPTs2RNHjx5VbWvevDl27dqFPn36oE2bNhg6dKiqR4myLEeMGFHjUNWTJ09iyJAhiIyMRFRUFF555RXcunVLtf3EiRMYMGAA2rZti759+2Lfvn1q79+yZYvqux01apRaTxZtec7Pz8eUKVPQrl07dOrUCfPnz0dxcXG1/BERmcJff/2Fjh07Ytu2bWqvOzlV3Lr9/vvvaq+/8MIL+PjjjwFUxJmMjAzEx8erpr9JS0vDqFGjVHFw3bp1aqNbd+3ahV69eiEyMhLPPfcczp49Wy1Pt2/fRs+ePREfH481a9Zg7dq1OH78eI1TAJSWlmLx4sXo3LkzWrdujbi4OLVjKS0txYIFC9CxY0d07NgRb731FnJzc1Xbr169ilGjRiE6Ohpdu3bFZ599pvb5X3/9NTp37ozo6GjEx8erYhoA7N+/H71790ZkZCQGDRqEv/76S2d5ExHZq3r16mHjxo2qhh2lwsJCxpR/MaYQkS1QKBT4v//7P7z44ouqhp3Kli5diilTpgDQ/pxEOUVmv3798PDDD+PKlStq1964uDh8+eWXGDx4MCIiIvDUU0/hzJkzqvenp6dj5MiRiIyMRN++fbFp0ya1pRC07VsQBKxfvx6PPPIIHnroIXz++eeIi4tT23flJQiqTq+m6/lQTe+rKY4dPHgQ/fv3R0REBGJjYzFp0iTcvXtX9X5N1/7vvvsO69atw19//WXwtJ47duxAr1690KZNG3Ts2BFz585VPa8DtD+fvHfvHmbNmqWKd++8845qmlVl2fft2xcRERF44YUXkJGRodp24cIFDBs2DG3btkXPnj3x5ZdfGpR/skICkY365ZdfhPDwcCEnJ6fG7d9//70QHh4ufP3110J4eLgwevRo4cKFC8J3330ntG7dWvjzzz8FQRCEgwcPCo8++qiQkJAgXL58WVi1apXQoUMHITc3VxAEQejWrZvQuXNnISUlRTh37pzw559/CuHh4YIgCEJ6eroQHh4uvPTSS8LVq1eFy5cvC7/++qvQpk0b4f/+7/+ECxcuCGPHjhXCw8OFb7/9VhAEQXjhhReENWvWCIIgCGPHjhXGjRsnXLlyRTh58qTw6KOPCl988YUgCIKwfPlyoVOnTsLhw4eF1NRUYejQocKECRNUeYqNjRX2798vXLp0SRg+fLjwzDPPCIIgCAqFQhgwYIAwffp0IS0tTfjzzz+FHj16COvWrRMEQRBKSkqENm3aCElJSYIgCEJ8fLywYsUKQaFQCA899JDw22+/CYIgCNOmTRPmz58vCIIgHD16VGjdurWwZcsW4dKlS8LmzZuFVq1aCX///bfqmFq3bi18++23wtWrV4VJkyYJjz76qKBQKARBEITw8HDhf//7n3D06FHh/PnzQq9evYRJkyYJgiAIt27dEsLDw4V9+/YJd+7cUSvf/Px8ISYmRli7dq1w7do14cSJE0KPHj1U+bp165bQrl074fPPPxeuXLki7Ny5U4iKihKOHz8uCIIgfP3110K7du2E77//Xrh8+bIwYcIE4emnnxaV5/HjxwtjxowRUlJShKSkJOGZZ54R4uPjDThTiYiMEx4eropZgiAIw4cPF8LDw4X+/fsLK1asEP7880+hrKxMtf3OnTvCY489JnzyySdCfn6+kJOTI3To0EGYNm2acPHiRWH//v1Cx44dhS1btgiCIAi//vqr0Lp1a+Grr74Srly5IsyfP1/o1KmTUFJSIkydOlWYOnWqcO/ePWHw4MHCq6++KpSVlQmFhYXCu+++Kzz77LPCrVu3hJKSErX4tnbtWqFHjx7C6dOnhWvXrgnvvfee0Lp1ayE7O1sQBEFYvHix8OyzzwpJSUlCSkqKMGbMGGH48OGCIAhCcXGxEBcXJ0yYMEG4cOGCcPDgQSEqKkpISEhQxYgRI0YI58+fF3777TchKipK+OqrrwRBEIRz584J0dHRwu7du4UrV64In376qdC2bVvhypUr5viqiIisXnl5ufDss88KY8eOFQSBMYUxhYhsxeXLl4Xw8HAhMTFRazpdz0mmTp0qtGjRQjh48KDquVDl+ka3bt2Ejh07qp43Pf/888Kzzz4rCIIg3L9/X3jiiSeECRMmCKmpqcLu3buFqKgooVu3bqL2/cUXXwjt27cXDh48KPzzzz/CwIED1Z7PdevWTfXsTBAEvZ4Pffvtt6p8VH5f1Th29epVoXXr1sK2bduE9PR04ciRI0LHjh2FzZs3C4Kg/dpfVFSkFq+U5Tl16lSN38eaNWuEF154QRAEQTh27JjQtm1bYd++fUJ6errw448/Cm3atBH27dsnCILu55Nvvvmm0Lt3b+HEiRPCmTNnhCeeeEJ49913Vd9hly5dhD///FNISUkR+vTpI7zxxhuCIAhCUVGR8NhjjwmrVq0SLl++LBw8eFB45JFHhP/7v//Tei6RbeC0bGSz8vLyAKDGHguVX8/Ly4O7uzveffdd+Pn5oVmzZvjrr7+wdetWdOzYERs3bsSYMWPQrVs3AMAbb7yBX3/9Fbt371aNJOnXr5+qVb6mBcpGjBiBBx98EEDFCKG+ffuif//+AIBFixahS5cuNeYxIyMDrVu3RoMGDdCwYUNs2LABderUgSAI2L59O6ZOnYrHHnsMADB37lz8+OOPqvcOGTIE3bt3B1DRE2HSpEkAKkbi3LhxAzt27ICTkxOaNGmCqVOnIj4+HuPGjYObmxvatm2Lv//+G23btsWxY8cwb948yGQytG/fHseOHcOjjz6KxMREvPHGGwCAL7/8Ej179sTIkSMBAI0bN0ZycjI2b96MlStXAgB69uyJAQMGAABeeeUV7N27Fzk5Oapegi+++CIefvhhVd6VvQSUQ1d9fHyqTVlXXFyM1157DS+++CJkMhlCQ0PRo0cP1ZpBX375JR555BG88MILAICGDRvi3Llz+PTTTxEbG4tt27Zh5MiR6N27NwBg1qxZ2LRpk2oEjqY837t3DwcOHMBff/0Fb29vABVTAPbv3x/x8fGq14iILGHDhg3YtGkTdu3ahY8++ggfffQRQkNDsWLFCkRGRsLX1xfOzs7w9vaGt7c3PvvsM3h6emL+/PlwcXFBWFgYsrOzsX79eowcORLbtm1Dnz59MGTIEADA22+/DVdXV1WcLS8vx5tvvgk3NzesXr0azs7OqF27NmrVqgVXV9capyBo0aIFHnroIURFRQEAxo4di/Xr1+PKlSuoXbs2vvjiC3z77beq2Lp06VJ07NgR58+fx/Xr13H79m0sWrQIXl5eaNasGWbOnKnqYQ4As2fPRuPGjREeHo5HHnkEKSkpAIBNmzZh8ODB6Nu3LwBg+PDhOH78OL7++muNi3gTETmSZcuW4ezZs/jmm28AMKYAjClEZBuUM7n4+PioXjt69CjGjRun+neDBg3w+OOPa31OAgARERFqo22qevrpp1XPm1588UW8/vrrACqeN2VmZmL79u3w8vJC06ZNceHCBXz//fcAdD+j+eabbzBixAjVvhctWqS6xuqi6/mQJlXjWE5ODmbOnInBgwcDAEJCQvDII4+o1jnVde2vKV7t2bOn2iwy7733nup5nlKtWrWwcOFC9OjRQ7XvLVu2IDU1FT169ND6fLJfv3746aefsGXLFtXyCfPmzVObxefVV19VrZs9aNAgbN26VZU/f39/1TO+Ro0aISMjA5999pnq2SXZLjbukM1SBjS5XI4HHnig2nbl0EwfHx+EhoaqphcDgFatWmHHjh0AKqYVWLZsmaqRAqhYxLryYmvBwcFa81J5e1paGp577jnVv/38/BAaGlrj+15++WVMnz4d+/fvx2OPPYbevXujVatWuH37NnJzc9G6dWtV2qZNm2LChAmqf1f+TG9vb9VQzLS0NOTm5qqtlaNQKFBcXIw7d+7Az88PsbGxSE5ORteuXZGVlYV27doBADp06ICffvoJeXl5uHLlCtq3b1/jMQEVC9RVXkSucn68vLwAQG14aMOGDdW2K6ef06ZevXro378/PvnkE5w7dw4XL17E+fPnVfm9dOkSDh06pLbw3/3799G4cWMAwOXLl9XKMCAgQG2BVk15TktLg0KhqBaIFQoFrl69ijZt2ujMOxGRqbi7u+O1117Da6+9hmvXruHQoUPYvHkzXn31VRw6dAju7u5q6dPS0tC6dWu1BT2jo6ORnZ2N/Px8XL58We0a7+bmpnat/PHHH1FWVoZevXrBzc1NVB67d++O33//He+++y4uXbqkmpKnvLwc6enpuH//frW4olAocOXKFaSnp6Nx48aq6zIADBw4EMB/HSyUHSqAihionEInLS0NP/74o9p0Pffv30enTp1E5ZuIyJ4tW7YMn376KVatWoXw8HAAjCkAYwoR2QZlB+b8/HzVa9HR0di5cycA4Oeff8bXX3+t8zkJoPsZV6NGjVT/X/n5zfnz56tdU6OiolSNO7r2fenSJbRs2VK1LTw8HLVr1xZ1/LqeD4nVqFEjuLm54YMPPkBqaipSU1Nx8eJFPPXUUwAMu/bHxcXhrbfeUnstMDCwWro2bdrAw8MDa9asUeX/6tWrqs/W9nzy6tWrKC8vV3vGFRsbq2qwA6rHM+UzuUuXLiElJUXteykvL6+2xAXZJjbukM2KiIiAs7Mzzpw5U2PjzpkzZ9C8eXO4ubmp9cwCKm72XV1dAVRc0KZPn64aVaJUOVhVrdRUVXW7UGWBNeW+qlLOcXrgwAH88ssvmDhxIl555RWMGjVK6/4AaLwIl5WVoUmTJtXW+gGgGnESGxuLd999F8ePH0ebNm3g6ekJoKJxZ9myZTh9+jSaNGmCunXr1nh8QEUZVp5bu6b8VC4HTWWgTVZWFgYOHIjWrVvjkUceweDBg/HLL78gKSlJdax9+/bF2LFj1d6nrGxWrnTWRFOey8vL4e3trdZ4pRQUFKT3cRARSWXfvn3IycnB0KFDAVTcwI8YMQKdOnVC7969cf78ebRt21btPZqu4UBFDNR1raxfvz7mzp2Ll19+GUePHsUjjzyiM5+rVq3Cjh07MGDAAPTv3x+zZ89W9dBTzin91VdfoVatWmrv8/f3V/Um16bq9VsZb8rLy/HKK69U64Hm4eGh8zOJiOzZ/Pnz8fXXX2PZsmXo2bMnAMYUJcYUIrIFDRs2hK+vL06fPq26Nnt6eqo60vr7+wPQ/ZwE0P2MS9PzG2dn52rPuyr/W9e+PTw8qr1fW0N/5bVodD0fEislJQVDhgxBXFwcYmNjMXLkSHz66adq+9T32l+7dm21Ds2aHDlyBOPGjUP//v3RuXNnjBs3DnPnzlXbt6bnkzWtLVRV1WefSmVlZXj44Ycxa9YsnZ9Btqfmb53IBtStWxfdu3fH+++/r3bBB4DMzEx88803qmGW6enpKCoqUm1PTk5GkyZNAFRMMXbz5k00bNhQ9ffhhx8iMTHRoHw1a9YMf//9t+rfhYWFuHr1ao1pV61ahZycHAwZMgQfffQR3njjDfz888+oU6cO/Pz8VFMCAMC5c+fw2GOPqaYU06Rx48a4ceMG6tatqzqe69evY82aNZDJZAAqendcu3YNx44dUw3ZVOa9Vq1a2LNnDzp06KD2mVUD5unTp9V6fpjC/v374ePjg48++ggjRoxAbGws0tPTVTcDjRs3xtWrV9W+u4MHD2LPnj0AKm5+KpfhnTt38NBDD+H69eta99u4cWMUFBRAJpOpPre4uBhLly5VW2CViMjcbty4gffff79aLFD25FM2ylfWuHFj/PPPP2ojJk+fPo26devC19e32rWyvLwccXFxOHnyJAAgJiZGVYGaP3++qJGXW7duxTvvvIO33noLvXv3VsVgQRAQGhoKZ2dn5Obmqq6xXl5eWLx4MXJyctCoUSNcvXpVLW4vWbIECxYs0Lnfxo0b4/r162pxYdu2bfj11191vpeIyF6tW7cOW7duxcqVK/Hkk0+qXmdM0Y4xhYisiYuLCwYOHIhPP/0UhYWF1bZnZWUB0P2cxBjNmjXDlStX1Pb/zz//qP5f176bNm2q9rwsMzNTNd0cUNGodPfuXdW/09PTVf+v6/mQWLt27UL79u2xYsUKDB06FG3btsXVq1fVnjNpu/Yrn6sZYseOHRg4cCDmzZuHZ555BmFhYbh27ZravjU9n1TGu8ox9sCBA3j66ad17rdx48a4fPkyQkJCVJ+bmJiIzz//3OBjIevBxh2yaTNmzEBeXh5eeeUVnDhxAjdu3MD+/fsxfPhwdOjQQdULraSkBFOnTkVqaiq2bt2Kffv2YcSIEQAq5g/99NNPsXPnTly7dg3Lli3Djz/+iLCwMIPy9MILL+DHH3/E9u3bkZaWhlmzZmlskLl06RLmzZuHlJQUpKam4vDhw2jVqhWAinV03nvvPfz5559ITU3FwoULERUVpbOnWKdOnRAcHIwpU6bg/PnzOHHiBN555x14enqqeqUp55v+6aef1Bp3lOvuHDx4UDUlGwCMHDkS+/btw6effoorV67gk08+wf79+1VzaZuKr68vbty4gT/++APp6enYsGEDfv75Z1UDy9ChQ3HmzBmsWrUKV65cwZ49e7By5Uo0aNAAQEUZfvrppzhw4AAuX76M2bNnIyQkBCEhIVr3GxYWhs6dO+Ott95CcnIy/vnnH8THx+PevXsa13giIjKHp59+Gi4uLnjppZfwxx9/4Pr16zh69CjefPNN9OjRQ3V9q1WrFi5duoTc3Fz07dsXpaWlmDVrFtLS0nDgwAGsXbsWQ4YMgUwmw7Bhw7B792783//9H65evYrFixdDEAS1If9AxZzPt2/fxpYtW3Tm09fXF4cOHUJ6ejpOnDiBt99+GwBQWloKLy8vPPPMM5gzZw6OHTuGixcv4u2338bVq1cREhKCTp06ISAgQJXfgwcPYuvWraKmwRk5ciR++OEHfPbZZ7h27Ro++eQTfPLJJ2pTSxAROZK0tDS8//77eOWVVxATE4Ps7GzVH2OKdowpRGRtJkyYgHr16uG5557DTz/9hPT0dCQnJ+Odd97BmjVrEBMTo/M5iTEefvhh1K9fH++88w7S0tLw008/4bPPPlNt17XvUaNG4bPPPsOPP/6ICxcuYPr06WqfHxERgW+++QYXLlzAsWPHsHnzZtU2Xc+HtKkcx3x9fXH+/HkkJyfj8uXLePfdd/H333+rPkfXtd/T0xO3bt3S2Wm4JsqRV+fPn0dqaiqmTZuG7Oxs1b61PZ/08vJC//79sXDhQiQnJ+Pvv//GqlWr8NBDD+ncb79+/VBcXKyKhYcPH8bChQtVo73ItnFaNrJpQUFB2L59O95//3289dZbuH37NkJDQ/Hcc89hxIgRqiGJLVu2RFBQEAYPHgw/Pz8sWrRItW5K7969IZfLsWbNGsjlcjRt2hQffPCBwTftsbGxWLx4MVavXo3bt29j4MCBanOKVjZnzhzMnTsXw4YNQ1lZGbp27YoZM2YAAEaPHo2CggK88cYbqm3vvPOOzv07Ozvjgw8+wPz58zF48GDUqlULvXr1UpvrWpnPCxcuqM25CVRMzbZv3z61xp3IyEgsXboUa9euxbJly9C4cWOsXr262lBRqT3xxBM4fvw4Jk6cCJlMhoiICEydOhVr165FaWkpgoOD8eGHH2L58uXYtGkTgoKCMG3aNPTr1w8A8NRTTyErKwtz585FYWEhOnTogDVr1oja99KlS7FgwQKMHDkSLi4u6Ny5M2bOnGnKwyUi0snX1xdfffUVVq9ejSlTpiA3NxcBAQHo27ev2mKqQ4YMwfLly3HlyhWsW7cOGzduxMKFC9G/f3/UrVsXI0aMwJgxYwAA7du3x+zZs7F+/XpkZ2ejTZs2+PDDD6t1JvD19cXEiROxfPlynQufLlq0CHPmzMGTTz6JoKAgPPPMM3B2dlaNQp02bRqWLFmCiRMn4v79+2jfvj02bNig6oTw/vvvY968eXj66acREBCAt99+G127dlWtj6BJVFSUKl4tXboUDz74IFasWKEW04iIHMnBgwdRXl6ODz74AB988IHatvPnzzOmaMGYQkTWxtPTE59//jk+/fRTvP/++7h69Src3NzQtm1brF27Ft27dwcArc9JjOHk5IS1a9finXfewVNPPYUmTZpgwIABqlEtup7RxMXF4c0338TChQtRUlKC8ePH4+jRo6rPf+ONNxAfH48BAwagSZMmeP311/Hmm28C0P18SJvKcWzp0qU4e/YsRo4cCXd3d7Rv3x7jxo1TrRuk69r/+OOPY+vWrXjyySeRkJCgV/mNHz8e8fHxePbZZ+Hl5YUuXbpgyJAhOHfuHADdzyenT5+OhQsX4sUXX4Srqyt69+6tKh9tvLy88PHHH2PRokXo378/fH198fzzz6tiN9k2maDv+DUiIiIiIiIiIiIichg5OTk4e/YsOnfurHpt48aNOHz4sMFTfDVv3hyfffaZ2qwyRCQep2UjIiIiIiIiIiIiIq1effVVfPXVV8jIyMDRo0fx6aefolevXpbOFpHD4rRsRERERERERERERKSRv78/Vq9ejffeew+LFy9GQEAAXnjhBdV610RkfpyWjYiIiIiIiIiIiIiIyIZwWjYiIiIiIiIiIiIiIiIbwsYdIiIiIiIiIiIiIiIiG8LGHSIiIiIiIiIiIiIiIhvCxh0iIiIiIiIiIiIiIiIbwsYdIiIiIiIiIiIiIiIiG8LGHSIiIiIiIiIiIiIiIhvCxh0iIiIiIiIiIiIiIiIbwsYdIiIiIiIiIiIiIiIiG8LGHSIiIiIiIiIiIiIiIhviYukM2LOcnAIIgqVzUTOZDPD397bqPIrFY7FOPBbrZAvHoswj/ceQ78sWvmux7OlYAPs6Hh6LdeKxqL+X/mPoOWFP55Q5sLz0xzLTH8tMP4wn0nP0Ooq5sMz0w/LSH8tMP8aWl9QxhY07JiQIsPofhS3kUSwei3XisVgnezoWR2DM92VP37U9HQtgX8fDY7FOPBaqythy5PegH5aX/lhm+mOZ6YflJR3WUcyLZaYflpf+WGb6sZby4rRsRERERERERERERERENoSNO0RERERERERERERERDaEjTtEREREREREREREREQ2hI07RERERERERERERERENsTF0hkgIvtTrhCQmJGHkuv5cFcoEBXsA2cnmaWzRUQ2iNcTIiIiInW8PyIiqo7XRnJEbNwhIkklpMqxIuEibhWWql4L9HLD5LimiGsWYMGcEZGt4fWEiIiISB3vj4iIquO1kRwVp2UjIskkpMoxdfdZtWAKALcKSzF191kkpMotlDMisjW8nhARERGp4/0REVF1vDaSI2PjDhFJolwhYEXCRa1pVh5KQ7lCMFOOiMhW8XpCREREpI73R0RE1fHaSI6OjTtEJInEjLxqvSSqyiooQWJGnplyRES2itcTIiIiInW8PyIiqo7XRnJ0bNwhIknIdQRTfdMRkePi9YSIiIhIHe+PiIiq47WRHB0bd4hIEgFebpKmIyLHxesJERERkTreHxERVcdrIzk6Nu4QkSQi6teBk0x7GidZRToiIm14PSEiIiJSx/sjIqLqeG0kR8fGHSKSxN+Z+dC1Pp1CqEhHRKQNrydERERE6nh/RERUHa+N5OjYuENEkuA8p0QkFV5PiIiIiNTx/oiIqDpeG8nRsXGHiCTBeU6JSCq8nhARERGp4/0REVF1vDaSo2PjDhFJIirYB4E6gmWQtzuign3MlCMislW8nhARERGp4/0REVF1vDaSo2PjDhFJwtlJhslxTbWmmdQtDM66VrojIofH6wkRERGROt4fERFVx2sjOTo27hCRZOKaBWBJv1bVek0EebtjSb9WiGsWYKGcEZGt4fWEiIiISB3vj4iIquO1kRyZi6UzQET2Ja5ZALqE+SMxIw8lTk5wVygQFezDXhJEpDdeT4iIiIjU8f6IiKg6XhvJUbFxh4gk5+wkQ+yDvggI8IZcXgBBsHSOiMhW8XpCREREpI73R0RE1fHaSI7IotOylZaWYu7cuWjfvj0eeeQRrFy5EsK/v7yzZ8/imWeeQWRkJAYOHIgzZ86ovXfv3r3o3r07IiMjMW7cONy+fVu1TRAELF++HA899BA6dOiApUuXQqFQqLbfuXMHEyZMQHR0NOLi4rBr1y61z9a1byIisj6MKUREJAXGEyIikgLjCRERmZpFG3cWLFiAo0ePYtOmTVixYgW2b9+Obdu24d69exg9ejRiY2Px3XffITo6GmPGjMG9e/cAAMnJyZgxYwbGjx+Pbdu2IT8/H/Hx8arP3bJlC/bu3Yt169ZhzZo12LNnD7Zs2aLaHh8fj4KCAmzbtg2vvvoqZs6cieTkZADQuW8iIrJOjClERCQFxhMiIpIC4wkREZmaxaZly83NxbfffostW7agbdu2AICXXnoJSUlJcHFxgbu7O95++23IZDLMmDEDv/76K3766ScMGDAAX3zxBZ544gn0798fALB06VJ069YN6enpCA0NxWeffYaJEyciNjYWAPDWW2/hvffew6hRo3Dt2jUcOnQIBw8eREhICMLDw5GYmIivvvoKbdu2xQ8//KB130REZH0YU4iISAqMJ0REJAXGEyIiMgeLjdw5efIkvLy80KFDB9Vro0ePxuLFi5GUlISYmBjIZBWLXslkMrRr1w6JiYkAgKSkJFUQA4D69eujQYMGSEpKQlZWFjIzM9G+fXvV9piYGGRkZODWrVtISkpC/fr1ERISorb99OnTqs/Wtm8iIrI+jClERCQFxhMiIpIC4wkREZmDxUbupKenIzg4GDt37sSHH36I+/fvY8CAAXj11VeRnZ2Npk2bqqX39/dHamoqAODWrVsIDAystv3mzZvIzs4GALXtAQEBAKDaXtN7s7KyAEDnvvXxb6y0Ssq8WXMexeKxWCcei3WyhWMxJG/2HlMMKRNb+K7FsqdjAezreHgs1onHYvh7GE+0v88ezilzYHnpj2WmP5aZfhhPrOOZF89b/bHM9MPy0h/LTD/GlpfU5Wyxxp179+7h6tWr2Lp1KxYvXozs7GzMmjULnp6eKCoqgpubm1p6Nzc3lJaWAgCKi4s1bi8uLlb9u/I2oGIxO12frWu7Pvz9vfV+j7nZQh7F4rFYJx6LdbKnYwHsP6YY833Z03dtT8cC2Nfx8FisE49Ff4wnpn2/o2F56Y9lpj+WmX4YT6zjmRfPW/2xzPTD8tIfy0w/1lJeFmvccXFxQWFhIVasWIHg4GAAwI0bN/D111+jYcOG1QJLaWkpPDw8AADu7u41bvf09FQLau7u7qr/BwBPT0+N79X12crt+sjJKYAg6P02s5DJKk5Ca86jWDwW68RjsU62cCzKPOrD3mOKId+XLXzXYtnTsQD2dTw8FuvEY1F/rz4YT2pmT+eUObC89Mcy0x/LTD+MJ9bxzIvnrf5YZvpheemPZaYfY8vLkJiijcUad+rVqwd3d3dVkAOAxo0bIzMzEx06dIBcLldLL5fLVUNLg4KCatxer149BAUFAagYaqqcY1Q5bFW5XdN7tX121WGtYggCrP5HYQt5FIvHYp14LNbJno4FsP+YYsz3ZU/ftT0dC2Bfx8NjsU48Fv0xnpj2/Y6G5aU/lpn+WGb6YTyxjmdePG/1xzLTD8tLfywz/VhLeTlZaseRkZEoKSnB5cuXVa9dunQJwcHBiIyMxOnTpyH8W0KCIODUqVOIjIxUvffkyZOq92VmZiIzMxORkZEICgpCgwYN1LafPHkSDRo0QGBgIKKiopCRkYGbN2+qbY+KilJ9trZ9ExGR9WFMISIiKTCeEBGRFBhPiIjIHCzWuNOkSRN07doV8fHxSElJwZEjR7BhwwYMGTIEvXr1Qn5+PhYuXIiLFy9i4cKFKCoqwhNPPAEAGDJkCHbt2oUdO3YgJSUFb7/9Nrp27YrQ0FDV9uXLl+PYsWM4duwYVqxYgeHDhwMAQkND0alTJ0yZMgUpKSnYsWMH9u7di+effx4AdO6biIisD2MKERFJgfGEiIikwHhCRETmIBMEyw0gKigowPz587F//354enpi6NChGDduHGQyGZKTkzF79mykpaWhefPmmDt3Llq1aqV673fffYc1a9YgLy8Pjz76KObPnw8/Pz8AQHl5OZYuXYrvvvsOzs7OGDRoECZPngyZTAYAyMnJwYwZM3D06FHUq1cPb775Jvr06aP6bF37Fksut965CmUyICDA26rzKBaPxTrxWKyTLRyLMo/6sueYYsj3ZQvftVj2dCyAfR0Pj8U68VjU36svxpPq7OmcMgeWl/5YZvpjmemH8cQ6nnnxvNUfy0w/LC/9scz0Y2x5GRpTNH6eJRt37J01/yjs6YfLY7FOPBbrZAvHInWgsweOXnGyp2MB7Ot4eCzWicei/l76Dxt3zIPlpT+Wmf5YZvphPJGeo9dRzIVlph+Wl/5YZvqxtsYdi03LRkRERERERERERERERPpj4w4REREREREREREREZENYeMOERERERERERERERGRDWHjDhERERERERERERERkQ1h4w4REREREREREREREZENYeMOERERERERERERERGRDWHjDhERERERERERERERkQ1h4w4REREREREREREREZENYeMOERERERERERERERGRDWHjDhERERERERERERERkQ1h4w4REREREREREREREZENYeMOERERERERERERERGRDWHjDhERERERERERERERkQ1h4w4REREREREREREREZENYeMOERERERERERERERGRDXGxdAaIyP6UKwQkZuSh5Ho+3BUKRAX7wNlJZulsEZEN4vWEiIiISB3vj4iIquO1kRwRG3eISFIJqXKsSLiIW4WlqtcCvdwwOa4p4poFWDBnRGRreD0hIiIiUsf7IyKi6nhtJEfFadmISDIJqXJM3X1WLZgCwK3CUkzdfRYJqXIL5YyIbA2vJ0RERETqeH9ERFQdr43kyNi4Q6RDuULAyfRc7Dt3CyfTc1GuECydJatUrhCwIuGi1jQrD6Wx/IhIJ15PiIjIVpUrBJy4lotdiRk4cY11B5IO74+IiKrjtZEcHadlI9KCwzrFS8zIq9ZLoqqsghIkZuQhJtTX6P0p51KVF5YiwMuNc6kS2RFzX0+IiIikwLqDYbhGgji8PyIiqo7XRnJ0bNwh0kA5rLMq5bDOJf1asZJWiVxHMNU3nTasOBPZN3NeT4iIiKTAuoNheF8vHu+PiIiq47WRHB2nZSOqAYd16i/Ay03SdJpwLlUi+1e3lquk6YiIiEyJdQfD8L5eP+aqbxER2RLWHcnRsXGHqAb6DOukClHBPgjUUZEI8nZHVLCPwftgxZnIMZQL4n7DYtMRERGZEusO+uN9vf7MUd8iIrI1rDuSo2PjDlENOKxTf85OMkyOa6o1zaRuYUbNn82KM5FjEPsb5m+diIisAesO+uN9vf7MUd8iIrI1rDuSo2PjDlENOOTdMHHNArCkX6tqPcqCvN0lmWecFWcixyC2UxU7XxERkTVg3UF/vK83jKnrW0REtoZ1R3J0LpbOAJE1Ug5519abjEPeaxbXLABdwvyRmJGHEicnuCsUiAr2kaQHGSvORI4hNtQXm4+li0pHRERkaaw76I/39YYzZX2LiMjWsO5Ijs6iI3f279+P5s2bq/1NnDgRAHD27Fk888wziIyMxMCBA3HmzBm19+7duxfdu3dHZGQkxo0bh9u3b6u2CYKA5cuX46GHHkKHDh2wdOlSKBQK1fY7d+5gwoQJiI6ORlxcHHbt2qX22br2TfbPEkPeyxUCTlzLxa7EDJy4lmvT80s7O8kQ+6AvnooKRuyDvpKVE+eZJm0YU+xHu1Bf1PHQ3v/Ex8MF7XiDTkQmwHhC+uJ0Wfrjfb1xTFXfImkxnhCZHuuO5Ogs2rhz8eJFdOvWDb/99pvqb8GCBbh37x5Gjx6N2NhYfPfdd4iOjsaYMWNw7949AEBycjJmzJiB8ePHY9u2bcjPz0d8fLzqc7ds2YK9e/di3bp1WLNmDfbs2YMtW7aotsfHx6OgoADbtm3Dq6++ipkzZyI5ORkAdO6bHIc5h7wnpMrR7+NjGLs9Ga9vTcTY7cno9/ExJKTKJduHPWDFmbRhTLEfzk4yzOgRrjXN9B7h/K0TkUkwnpAhOF2WfnhfT46A8YTI9Fh3JEdn0WnZ0tLSEB4ejnr16qm9/s0338Dd3R1vv/02ZDIZZsyYgV9//RU//fQTBgwYgC+++AJPPPEE+vfvDwBYunQpunXrhvT0dISGhuKzzz7DxIkTERsbCwB466238N5772HUqFG4du0aDh06hIMHDyIkJATh4eFITEzEV199hbZt2+KHH37Qum9yLJWHvMsLSxHg5Sb5kPeEVDmm7j5b7fVbhaWYuvssK4NVKCvOKxIuqk19EeTljklxYSwrB8aYQkREUmA8IUNxuiwyl3KFUHGeXc/neWbFGE+IiMjULDpyJy0tDY0aNar2elJSEmJiYiCTVdycyGQytGvXDomJiartyiAGAPXr10eDBg2QlJSErKwsZGZmon379qrtMTExyMjIwK1bt5CUlIT69esjJCREbfvp06dF7Zscj7OTDDGhvujZMhAxodIOeS9XCFiRcFFrmpWH0mx6ijZTEaqshqcQFBpSkqNgTLEfvDYSkSUxnpAxOF2WOIz1huOsD7aD8YTI9BhPyNFZrHFHEARcvnwZv/32G3r27Inu3btj+fLlKC0tRXZ2NgIDA9XS+/v74+bNmwCAW7duadyenZ0NAGrbAwIqevIrt9f03qysLADQuW8iKSVm5GldeBUAsgpKkJiRZ6YcWT/lSKfsu/fVXs++ex9Td59lpcZBMabYF14bichSGE+IzIOx3jDKulDVslPO+sC6kPVgPCEyD8YTcnQWm5btxo0bKCoqgpubG1avXo3r169jwYIFKC4uVr1emZubG0pLK36sxcXFGrcXFxer/l15GwCUlpbq/Gxd2/Uhs+JOWsq8WXMexbLlY5HfFXdeye+W2tzxmeJ7Edsjo2tTf0l7SdryOVaVLRyLIXmz95hiSJnYwnetya3CEtHpbPH4bPm7qYrHYp14LIa/h/FE+/vs4ZwyB5aXbvZcDzIVS9WF7AXjiXU88+L1UX8sM+3sve5oDjzH9GNseUldzhZr3AkODsaxY8fg4+MDmUyGli1bQqFQYMqUKejQoUO1wFJaWgoPDw8AgLu7e43bPT091YKau7u76v8BwNPTU+N7dX22crs+/P299X6PudlCHsWyxWMJayDuBiqsgS8CAmzv+ABpv5c/0nJE9ci4VHAfD4f5S7ZfJVs8xzSxp2MB7D+mGPN92eJ3fV+WLTKdk81eGwHb/G404bFYJx6L/hhPTPt+R8Py0swR6kFSs3RdyF4wnljHMy9eH/XHMquZo9QdzYHnmH6spbws1rgDAL6+vmr/DgsLQ0lJCerVqwe5XH04sVwuVw0dDQoKqnF7vXr1EBQUBKBiqKlyjlHlsFXldk3v1fbZVYetipGTUwDBSqd0lMkqTkJrzqNYtnwsTbxdEejlpvUmPcjbHU28XSGXF5gxZ8YzxfeSdiNXdLpmPm66E4pky+dYVbZwLMo86sueY4oh35ctfNeauIpcQ8tVUNjctRGw7e+mKh6LdeKxqL9XX4wn1dnTOWUOLC/d7LkeZCqWqgvZC8YT63jmxeuj/lhm2tl73dEceI7px9jyMjSmaGKxNXeOHDmCjh07oqioSPXauXPn4Ovrq1rsTblguiAIOHXqFCIjIwEAkZGROHnypOp9mZmZyMzMRGRkJIKCgtCgQQO17SdPnkSDBg0QGBiIqKgoZGRkqM0nevLkSURFRak+W9u+9SEI1v1nC3m092NxkskwOa6p1vNoUrcwOMlkFs+rNXwvAbXFVVICartZ/bHY0/diqjzqw95jij1/1zX9BXq5iyqXQC93i+fV0b4bHovt/PFY/nuvPhhPHOOcsvbz1hH+7L0eZIo/S9aF7OXPmN+lvuw9nlS81/zfg6P+scw0/zlC3dEcfzzHzFteUrJY4050dDTc3d0xc+ZMXLp0CYcPH8bSpUvx8ssvo1evXsjPz8fChQtx8eJFLFy4EEVFRXjiiScAAEOGDMGuXbuwY8cOpKSk4O2330bXrl0RGhqq2r58+XIcO3YMx44dw4oVKzB8+HAAQGhoKDp16oQpU6YgJSUFO3bswN69e/H8888DgM59E0ktrlkAlvRrhUAv9Zv1IG93LOnXCnHNAiyUM+sTFexTrZyqCvJ2R1Swj5lyRNaCMcW+8LdORJbCeEJkPqwH6Yf3R7aF8YTIPHhtJEcnEwSp24vES01NxaJFi5CYmIjatWvjueeew7hx4yCTyZCcnIzZs2cjLS0NzZs3x9y5c9GqVSvVe7/77jusWbMGeXl5ePTRRzF//nz4+fkBAMrLy7F06VJ89913cHZ2xqBBgzB58mTI/l2xKCcnBzNmzMDRo0dRr149vPnmm+jTp4/qs3XtWyy53HqHs8lkQECAt1XnUSx7OZZyhYDEjDyUODnBXaFAVLCPTS+EaarvJSFVjqm7z2rcboqKoL2cY4BtHIsyj/qy55hiyPdlC9+1Npb4rZuLrX83lfFYrBOPRf29+mI8qc6ezilzYHnpx97qQaZkz/dHpsZ4Yh3PvHh91B/LTDdeG43Dc0w/xpaXoTFF4+dZsnHH3lnzj8Kefrg8Futj6gpaQqocyw+mIvvufdVrgV5umBzX1CQB216+F8A2jkXqQGcPHLXilJAqx7IDFyC/V6Z6rV5tV7z1v2Y2fXNuD9+NEo/FOvFY1N9L/2HjjnmwvPTDxh39mLsuZC8YT6Snb1nyt24YxhRxeG00HM8x/Vhb446LZJ9EREZR3ehcz7fpG52EVDlWJFxUWxzVFAFV2SuJiOzXmRv5uF1UpvZazr37OHMjnzfoREREdsBcdQd7w7oQ2Rr+1sksqlwb2U5BjsBia+4Q0X8SUuXo9/ExjN2ejNe3JmLs9mT0+/gYElLlls6aXpRDYSvfsAHArcJSTN19VpLjMcc+iMjy1hy+hM9PXIeiyh25QgA+P3Edaw5fskzGiIiISBK8r9cfy4xsEc9bMjXlOZZdCnNgRgABAABJREFU5RzL5jlGDoCNO0QWZi83OuUKASsSLmpNs/JQGsqrPqm1sn0QkeWVlinwxYnrWtN8ceI6SssUZsoRERERSalcIWDRzxe0pln08wXe11fCuhDZIp63ZGqMJ+To2LhDZEH2dKOTmJFXrYGqqqyCEiRm5Fn1PojI8rafztA5hF74Nx0RERHZnpPpucgrLtOaJq+4DCfTc82TIRvAuhDZIp63ZGqMJ+To2LhDZEH2dKMj13Ec+qaz1D6IyPKSboi75olNR0RERNbl1PVcSdM5AtaFyBbxvCVTYzwhR+di6QwQOTJ7utEJ8HKTNJ2l9lFVuUJAYkYeSq7nw12hQFSwD5yduIApkSl5ujpLmo5Mg9dHIiIylCByYgKx6RyBJepCRMbieUumxnhCjo6NO0QWZE83OhH168BJhmqLn1fmJKtIZ6ioYB8EerlpHe0U5O2OqGAfg/dRWUKqHCsSLqrtL9DLDZPjmiKuWYAk+yCi6nq1DMSP57JFpSPL4PWRiIiMERvqi83H0kWlowrmqG8RSc3cdXhyPNEhPoCIeBIdwnOM7BOnZSOyIOWNjja2cqPzd2a+1ooGUFER+Tsz3+B9ODvJMDmuqdY0k7qFSdJzPCFVjqm7z1a7Cb1VWIqpu88iIVVu9D6IqGauTuJuT8SmI2nx+khERMZqF+qLOh7a+5r6eLigHRt3VMxR3yKSmjnr8OSYnGXizh2x6YhsDZ+KEFmQPd3o2NMUc+UKASsSLmpNs/JQGsp11a6IyCC3792XNB1Jh9dHIiKSgrOTDE+1eUBrmn5tHrCJepC53CookTQdkbnENQvAkn6tqnVsDfJ2x5J+rTjqm4wivyvyWZTIdES2htOyEVmY8kan6vQ2Qd7umNQtzGZudMwxxZzYh4pdwvyNqggmZuRpHTYOAFkFJUjMyEMMexMSSa5uLVdJ05F0eH0kIiIplCsE7Eu5pTXNz+ezMa5zYzbw/OtOkbhOLWLTEZlTXLMAdAnzr1iv0cmJ6zWSZHLuiWu0EZuOyNawcYfICtjDjY455tI110NFexqFRGSLxI754NgQ8+P1kYiIpMDOAvrz8xTXqUVsOiJzc3aSIfZBXwQEeEMuL+AC9ySJ/KIySdMR2RpOy0ZkJZQ3Ok9FBSP2QV+batgBzDPFnLkeKppjFBIRaXZH5HRrYtORdHh9JCIiKbCzgP4Cvd0lTUdEZA/ELsPK5VrJXvHUJiLJmHouXXM9VFSOQtLG2FFIRKQZGxCsF6+PREQkBcZ6/TEGExFV1y7EV9J0RLaG07IRkaRMOcWcOaZ+A/4bhTR191mNaYwdhUREmpnrt0764/WRiIikwFivP8ZgIqLqYkJ94ePhgrxizdOu+Xi4cIpPslscuUNEkjPVFHPmmPpNydSjkIhIM3P+1kl/vD4SEZGxGOsNwxhMRKTO2UmG6T3CtaaZ3iOc8YTsFkfuEJFNUVZoViRcVOvpF+TtjkndwiSt0JhyFBIRaWfO3zrpj9dHIiIyFmO9YRiDiYjUaYwnXu6YFMd4QvaNjTtEZHMqV2jkhaUI8HIzWYVGOQopIMAbcnkBBEHyXRCRBnx4Yd14fSQiImMx1huGMZiISB3jCTkqNu4QkU1ydpJxzlQiB8CHF0RERPaNsZ6IiKTAeEKOiGvuEBERERERERERERER2RA27hAREREREREREREREdkQg6ZlS0tLQ2BgILy9vXHkyBEkJCSgVatWeOaZZ6TOH5HDKFcIFXODXs/n3KDkMK5evQJ//wB4eXnh2LE/8Ntvv6J58+Z48cVhls4aWQleG4lIrKox5ffff0W7dpGsoxBZOcZ6sjaMJ0S2ifGEHJHejTvbtm3DvHnzsGXLFnh5eeHVV1/FQw89hP379+PGjRt4/fXXTZFPIruWkCrHioSLuFVYqnot0MsNk+OaIq5ZgAVzRmQ6u3Z9h5Url2D16vdRu3ZtTJs2Ce3atcevvyYgP/824wnx2khEotUUU2Ji2uPIkV9YRyGyYoz1ZG0YT4hsE+MJOSq9p2XbuHEjlixZgg4dOuDbb79Fy5YtsXHjRqxatQo7duwwRR6J7FpCqhxTd59VC0AAcKuwFFN3n0VCqtxCObNu5QoBJ9Nzse/cLZxMz0W5givl2ZqvvvoMM2fORXR0DL7/fjeaNg3HihVrMG/eYsYT4rWRiPSiKaawjkJkvRjrDVeuEHDiWi52JWbgxDXWhaTEeEJkexhPyJHpPXInKysLMTExAIBDhw7h2WefBQA88MADuHv3rrS5I7Jz5QoBKxIuak2z8lAauoT5cyhpJeyRYR+ys7PRtm0UAOD334/gqacGAADq1QtkPHFwvDYSkb40xRTWUYisE2O94VgXMi3GEyLbwnhCjk7vkTtNmjTBnj178M033+DGjRvo3r077t+/j82bN6NFixamyCOR3UrMyKvWs6CqrIISJGbkmSlH1o89MuxHw4YN8fPPP2Hv3l3IyrqJzp27oqysDFu3fsl44uB4bSQifWmKKayjEFknxnrDsC5keownRLaF8YQcnd4jd6ZOnYo33ngDeXl5GDp0KMLCwjBv3jzs378fH374oSnySGS35DoCkL7p7B17ZNiX8ePfxKxZ05Cfn4+nnx6ERo0aY+XKJTh8+BA2bPjI0tkjC7pVUCJpOiKyf5piypEjv7COQmSFWA/SH+tC5sF4QmRbWHckR6d3487DDz+MP/74AwUFBfDx8QEAvPbaa4iPj4erq6vkGSSyZwFebpKms3f69MiICfU1T6bIYDEx7bFnz34UFhaiTp06AICRI1/G669PxgMP+Fk4d2RJd4ruS5qOiOxfTTHlxRdfxrx5s1lHIbJCrAfpj3Uh82A8IbItrDuSoxM1Ldvx48dRVlam+v+TJ0/iwoULOH78OI4fP47Lly8jMTERx48fNzgjo0ePxrRp01T/Pnv2LJ555hlERkZi4MCBOHPmjFr6vXv3onv37oiMjMS4ceNw+/Zt1TZBELB8+XI89NBD6NChA5YuXQqFQqHafufOHUyYMAHR0dGIi4vDrl271D5b176JpBIV7INAHRWWIG93RAX7mClH1o09/GxfYuIpVTxJTDyF5OREXLp0EYmJp5CYeArXrl3FmTPJjCcOzs9TXMVZbDoisk9iYgrrKETWifUg/bEuZDqMJ4wnZLtYdyRHJ2rkzrBhw/D777/D398fw4YN05hOJpPh3Llzemfi+++/x+HDh/H0008DAO7du4fRo0ejb9++ePfdd/H1119jzJgx2L9/P2rVqoXk5GTMmDEDc+fORYsWLbBw4ULEx8fjo48qpvHZsmUL9u7di3Xr1qGsrAxTpkyBv78/Ro0aBQCIj49HcXExtm3bhqSkJMycORONGzdG27Ztde6bSErOTjJMjmuKqbvPakwzqVuYZMPqyxUCEjPyIC8sRYCXG6KCfWxqyD57+Nm+CRPGYPfuffDzq4sJE8ZoTMd44tgCvd0lTUdE9okxhTGFbJe560H2gHUh02E8MU88UT6PKLmeD3eFwuaeR5B1Yt2RHJ2oxp2UlJQa/18Kubm5WLp0KSIiIlSv/fDDD3B3d8fbb78NmUyGGTNm4Ndff8VPP/2EAQMG4IsvvsATTzyB/v37AwCWLl2Kbt26IT09HaGhofjss88wceJExMbGAgDeeustvPfeexg1ahSuXbuGQ4cO4eDBgwgJCUF4eDgSExPx1VdfoW3btjr3TY7H1A0icc0CMCw2BF+evA6F8N/rTjLg+ZgQxDULkGQ/CalyrEi4qDaUP9DLDZPjmkq2D1NT9vDTNh0Be/hZtyNHjtf4/5XJZEBAgLfen814Yj/4WyciMXTFFEPjCcCYQmQOcc0C0CXMH4fTcqpt6xLmbzN1FHPh/ZHpMJ6YPp7Yw/MIsk68NpKjEzUtW1Xl5eX45Zdf8MknnyA/Px9JSUkoKCgwKANLlizBU089haZNm6peS0pKQkxMDGSyigfoMpkM7dq1Q2Jiomq7MogBQP369dGgQQMkJSUhKysLmZmZaN++vWp7TEwMMjIycOvWLSQlJaF+/foICQlR23769GlR+ybHkpAqR7+Pj2Hs9mTM/CEFY7cno9/Hx5CQKpd0H5+fUG/YAQCFAHx+4rok+0pIlWPq7rPVgt2twlJM3X1W0uMBKhrETlzLxa7EDJy4lovyqgdnIGUPP23Yw8+2lJeX4+jR37B9+1coKCjAP/+cQWFhoUGfxXhiP5ydZGgZpL0C3SLQi791IlJTU0xhHYXIeq05fKnGhh0AOJyWgzWHL5k5R9aNdSHzYTyRlrmfR5BjcXaSoWeLQK1pejSvx2sj2S1RI3cqy8zMxEsvvYS8vDzk5eXhf//7HzZu3IjTp09j48aNaNGihejP+uOPP3DixAns2bMHc+bMUb2enZ2tFvgAwN/fH6mpqQCAW7duITAwsNr2mzdvIjs7GwDUtgcEVPQCUG6v6b1ZWVmi9q0PmRVfN5R5s+Y8imWqY0m4IK9xmgDlDcjSfq0QF25cD5NyhYAVCRe1pll5KA1dm/obHIjMsY/KEi7IsbyGHjlvxTU1urwA4H/hAVjar1W1fQR5u2NytzBJ9lEVfy+mkZV1E2++OR75+fnIz89Dp06P4auvPsWZM8nYvHkz40klhnxf1vRd66u0TIFfNTzsUfo1LQf3yxVwczGon4pF2fJ3UxWPxTo54rFoiikzZpxhHaUSQ88JezqnzIHlpVtpmQJfnLiuNc0XJ67j1U6NbDLWm8r/wrXP+vA/E9SF7AXjiWXqKOZ+HmGPGFO0K1cI2HXmptY0u8/cxPjHGvMc04DnmH6MLS+py1nvxp158+YhNjYWc+bMUfUkWLlyJWbMmIGFCxfi888/F/U5JSUlmD17NmbNmgUPDw+1bUVFRXBzU58n1s3NDaWlFQ9yi4uLNW4vLi5W/bvyNgAoLS3V+dm6tuvD39+wYbvmZAt5FEvKYylXCFh1+C+N22UAVh2+hIEPNTIqOPyRlqN16CgAZBWU4FLBfTwc5m+1+1D66Uwmpu4+i6rjdLL/bRD74IV26NWmvlH7AIA6NwvhVKXcZTKgTh0Pg4fLi8Hfi7TeeedtdOzYQRVP6tb1wvr1axlPamDM92UN37W+Pv71UrXrSFUCgO8v5OCVx5qYI0smYYvfjSY8FuvkSMdSU0xZt44xpSpjzwl7OqfMgeWlmaPEeqn9dCYTn9fQKKac9eHRFoGS1LfsGeOJeeso5nweYe8YU2r2e6oc+cVlWtPkFZfhYl4pHuUUgFrxHNOPtZSX3o07J06cwPbt2+Hs7Kx6zdXVFa+99ppqcTgx1q1bhzZt2qBz587Vtrm7u1cLLKWlpaqAqGm7p6enWlBzd3dX/T8AeHp6GvzZVYOxGDk5BRCkmY1KcjJZxUlozXkUyxTHcuJaLjLzijVuFwBk5hVjf+J1xD7oa/B+0m7kik7XzMewhTHNsQ+gokFs1s4zNVbSlK/N3vUPogNrG9UglnBBjrdrGFF1M78EY784JcmIqqr4ezGN48ePY8OGT3Dnzj0IAnD7diE8PYsxdOgIvPjiC6I/h/GkZtb0XevryHntPa8qp3u6VT0T50Z6tvzdVMVjsU6OeCw1xZRatYpZR6nC0HPCns4pc2B56fbbhSzR6Wwx1ptCuULA1G+StaaZ+k2y0fUte8V4Ypk6irmeR9gzxhTt9p/JEJ2uuZ+7iXNjm3iO6cfY8lK+Xyp6N+54eHggJycHjRs3Vnv98uXL8PLyEv0533//PeRyOaKjowH8F4z27duHPn36QC5Xn3NTLperhpYGBQXVuL1evXoICgoCUDHUVDnHqHLYqnK7pvdq++yqw1rFEARY/Y/CFvIolpTHItfRs6RyOmP2GVBb3M1LQG03g/djjn0AwOnreaJ65Jy+noeYUF+D9lGuELBcx5DuFYfS8FiYaYZ08/ciLXd3D9y+fRuhoQ3V8nT16lXGkyqM+b6s4bvWV9H9ctHpbO3YKrPF70YTHot1cqRj0RRTWEdRZ+w5YU/nlDmwvDSr7eqsO9G/6ViGFU5cy0WeiN7pJ67lokNDPzPlyvYwnpi3jmKu5xGOgDGlZjfzNXfMrpqO5acdzzH9WEt56T157XPPPYdZs2bhl19+AVAR4L799lu88847GDRokOjP+fzzz7Fnzx7s3LkTO3fuRFxcHOLi4rBz505ERkbi9OnTEP4tIUEQcOrUKURGRgIAIiMjcfLkSdVnZWZmIjMzE5GRkQgKCkKDBg3Utp88eRINGjRAYGAgoqKikJGRgZs3b6ptj4qKUn22tn2TYwjwEnkDIjKdJlHBPgjU8RlB3u6ICvax6n0A+jWIGSoxQ1wDUmJGnsH7IPPp338gli1bhKNHfwMgID39Gr7/fjeWLFnAeOLg6nqKu7aKTUdE9k9TTGEdhcg6PdEqSNJ0juDU9VxJ01HNGE+kZa7nEeTABJEde8WmI7Ixeo/cGTduHOrUqYM5c+agqKgIo0ePhr+/P0aOHIlRo0aJ/pzg4GC1f9euXRsA0LBhQ/j7+2PFihVYuHAhnnvuOWzduhVFRUV44oknAABDhgzBsGHDEBUVhYiICCxcuBBdu3ZFaGioavvy5cvxwAMPAABWrFiBl156CQAQGhqKTp06YcqUKZgxYwb+/vtv7N27F1988QUAoFevXlr3TY5BeQOirSFBihsQZycZJsc1xdQaphlTmtQtzKhRKObYBwD41XKVNF1NzNGAROYzcuTL8PLywvLli1FcXIwpU16Hn19dPPfcUEyY8Jroz2E8sT8P1PGUNB0R2T9NMeWll15kHYXICrUL8ZU0nSMQ2zvYGnoR2zLGE2mZ63kEOa4gb3FTCopNR2Rr9G7c2bt3L/r27Ythw4bh3r17KC8vh7e3tAsIeXl54aOPPsLs2bOxfft2NG/eHBs2bECtWrUAANHR0Zg3bx7WrFmDvLw8PProo5g/f77q/aNGjUJOTg7Gjx8PZ2dnDBo0CCNHjlRtX7p0KWbMmIHBgwejXr16WLRoEdq2bStq3+QYzHkDEtcsAEv6tcKKhItqjUlB3u6Y1C0McRIs+GaOfYgtCWNKzFwjqsg89u//CT16PIFBg55DUVERysvL4eXlBZkMcHLSe2BpjRhPbJNvLXG3J2LTEZH9qymmeHt7ISBAunoKYwqRdP7OzBedztApne1NbKgvNh9LF5WODMd4Ij3l84jlB1ORffe+6vVALzdMjmsqyfMIclysO5KjkwmCfv062rdvj23btqFJkyamypPdkMutdyEqmQwICPC26jyKZcpjWXP4Er48eR2KSp/rJAOejwnBxC7S/gbKFQISM/JQ4uQEd4UCUcE+kvdeUe5DXliKAC83Sfex79wtzPwhRWe6Bb1boGdL/efzBSry3+/jYzpHVO16uYOkZcffi2n06tUNGzZswYMPNlJ7XZlH+o8h35c1fdf6+vFsFmb9eF5nunlPNLfJ6Vps+bupisdinRzxWGqKKYwn1Rl6TtjTOWUOLC/dzFF3sDflCgE9PvgD+VrW3fHxcMG+Vx/mKIgaMJ5IT59rXEKqvFpnUzbuiMOYop291x3NgeeYfowtL6ljit5dozt27Ii9e/eqFoMjslcJqXJ8fkK9YQcAFALw+YnrSEiV1/xGAzk7yRD7oC+eigpG7IO+Jrkhd3aSISbUFz1bBiImVNp9mGNUjXJElTYc0m072rWLxf79+xhPqJpAb3dJ0xGR/WNMIbItHJGvP2cnGZ5q84DWNP3aPMC6kJEYT6SXkCrH1N1nq3XSvFVYiqm7z0r+bIUcC+uO5Oj0HpOWk5OD999/Hx9++CHq1q0Ld3f1H8fBgwclyxyRpZQrBKxIuKg1zcpDaegS5s+b539F1K8DGQBtjdayf9MZwxxTzJF53LlzG598shGffbYZvr5+cHOriCcV07LJGE8cWKsgcb1YxKYjIvtXU0xRxhOAdRQia2OuuoM9KVcI2JdyS2uan89nY1znxqyjGoHxRFp8tkKmxnhCjk7vxp3Bgwdj8ODBpsgLkdVIzMjTOvUXAGQVlCAxI49zQP8rKSNPazAFKoJtUkYe2jf0M2pfcc0C0CXM32RTzJF59Ov3NPr1e7rGbd5c7NChfZt8Q3S6F2JDTZwbIrIFmmIK4wmRdTJn3cFesI5qHown0uJ5S6bGeEKOTu/GnaefrghyhYWFuHLlCpycnNC4cWN4enpKnjkiS5HruPnQN50YqjV3ruebbM0dUzqRnis6HQMqAcATT/QBANy7dxfXrl2Dk5MMDz7YCJ6eHpzT2sElXhe3yHLi9Xy8EGvizBCRTagppjRs2AghIfUsnDNyNLZ+T28urDvozxJ1VEfEeCItnrdkaown5Oj0btwpKirCrFmz8OOPP6KsrGIhPzc3Nzz99NOYOXMmXF1dJc8kkbmZew5oe1hcUOwiYlIszmYP5UVAcXExli1biIMH96O8vBwA4Orqht69+2DBgrmMJw7M01XckoBi0xGR/dMUUwYMYB2FzIf3qOLJRLZ3iU3nCPxqibuOiU1HNWM8kRbPWzI1xhNydHo/FXnnnXeQkpKCTZs24eTJkzh+/Dg+/PBDnDhxAosXLzZFHonMLirYB3U8tLd9+ni4ICrYx+h9mXNxwXKFgJPpudh37hZOpueiXCFBS8u/fHSUl77pNOFijPZj6dKFuHgxFStXrsO+fYfx44+HsGTJSiQmnmY8cXDhgbUlTUdE9q+mmLJ06UrWUchseI+qn3YhvpKmcwRin0vy+aVxGE+kxfOWTI3xhByd3o07CQkJePfdd9GxY0fUrl0b3t7eeOSRR7Bo0SLs3bvXFHkksghz3FyIXVxQikaYhFQ5+n18DGO3J2PmDykYuz0Z/T4+JllFs25tcaOYxKariTnLi0zvt99+xfTpc9CuXSxq1aoFLy8vtG/fEdOnz2I8cXC6Gtf1TUdE9k9TTGEdhcyB96j6iwr20Vnfkv2bjirI74qc3kpkOqoZ44m0bhWWSJqOqCrGE3J0ejfu+Pv7Iycnp9rrpaWl8PLykiRTRJaWmJGHvOIyrWnyisuQmJFn9H7ELi5oDHP0JAz0dpc0XU3MVV5kHn5+frhz53a11+/fZzxxdL+mVT8vjElHRPZPU0xhHYXMgfeo+vs7M1/UAth/Z4pbh88R3Cm6L2k6qhnjibTOZBZImo6oKsYTcnR6d3kdM2YMZsyYgTFjxiA6OhouLi44d+4c1qxZg6effhrHjx9XpW3fvr2kmSUyF3Mt+meO/YjtSdglzN+oxV6jgn0Q6OWmtWIb5O1uVG8JLsZoX4YNexHvvjsfw4aNRJs2kXBxcUFq6nls2vQRBg4cwHjiwIpLyyVNR0T2r6aYcvHieWzevIF1FDI53qPq71aByN78ItM5Aj9PkWuXiExHNWM8IbItjCfk6PRu3Jk5cyYAYMGCBdW2rV+/HuvXrwcAyGQynDt3zsjsEVmGj6fI9WNEptOkrshFA8Wmq4k+PQljQn0N3o+zkww9WwTi8xPXNabp0byeUQ1IAV7ipnQTm44sa8mSijiyevXyatsYTxybm7O06YjI/jGmkCXxHlV/2XfFPWQTm84RBIic3lpsOqoZ44m0gn09JE1HVFW2yCn9xKYjsjV6P5lOSUkxRT6IrEpa9l3R6R5qVNfg/YiddduY2bnN1ZOwXCFg15mbWtPsPnMT4zo3NriBxxyjg8h8jhw5XuPrMhkQEOBt5tyQNblXJu6qJzYdEdm/mmIK4wmZC+9R9Xchq1DSdI7AHHVHYjyRWtOA2pKmI6rqQrbIeCIyHZGt0XvNHQBIS0tDQUHFfJhHjhzB3LlzsWPHDkkzRmRJGfniWvTFptPkzj2R8yaLTFcTbw9xXdvFptPkVHou8kWsU3QqPdfgfTg7yTA5rqnWNJO6hRk1OojM6+rVKygsrLjJOnbsD6xYsQR79uy0bKbI4rJEXlvFpiMix1BTTGEdhcyB96j6y8grljSdIzBH3ZEqMJ5Ih+ctmVpGrsh4IjIdka3Ru3Fn27Zt6NevH86dO4ezZ8/i1VdfRXp6Ot577z289957psgjkdmFiBwSLDadJuaYwuGXi3JJ02lyQmSjjdh0msQ1C8CSfq0QWKVMgrzdsaRfK8Q1CzDq88l8du36DsOHP4vU1PO4cCEF06ZNwo0bGfj44w8YTxxcQYm4yp3YdERk/zTFFNZRyFx4j6qfrHxxD9nEpnMEnP7PPBhPpHWnSGTjjsh0RFXl3RM3C43YdES2Ru9p2TZu3IglS5agQ4cOmD9/Plq2bImNGzfi+PHjePPNN/H666+bIp9kY8oVAhIz8iAvLEWAlxuign1sqqfa0xH1seqXS6LSGcMcUzik3BQ3xZzYdJoIIicAEJtOm7hmAegS5m/T5xgBX331GWbOnIvo6BisWrUUTZuGY8WKNUhKOoU5c2YwnjgwsT1PDBp+TER2SVNMuXw5hXUUMpvK96glTk5wVyh4j6pBmUJcnUBsOkcQUb8OnGSAtiJxklWkI8MxnkjLx0PkesYi0xFVIxMZY8WmI7Ixel89s7KyEBMTAwA4dOgQnn32WQDAAw88gLt3jXs4TPYhIVWOFQkX1RosAr3cMDmuqc30WDubVSA6XUyor8H7cXaSoWWQN24V5mhM0yLQy6gKobfImySx6TSp4+4qaTpdnJ1kRpU9WV52djbato0CAPz++xE89dQAAEC9eoGMJw7O1cUZKFGIS0dEBM0xhXUUMjdnJxliH/RFQIA35PICCGybqJGXuyvuFJeLSkcV/s7M19qwA1Q0/Pydmc96khEYT6SVp2Pqdn3TEVVVy80FgO7puivSEdkfvc/sJk2aYM+ePahbty5u3LiB7t274/79+9i8eTNatGhhijySDUlIlWPq7rPVXr9VWIqpu8/azJQEci0jaQxJp0lpmQK/pmlu2AGAX9NyUFqmgJuLYX3Uh8Q0wF/XckWlM4Z/bXHD/8WmI/vXsGFD/PzzT/Dz80NW1k107twVZWVl2Lr1S8YTB9fUvxay7+aJSkdEBGiOKayjEFmnRxr7YVtipqh0VMFcdVRHx3giLY7cIVOLfdAX57N1N7zGPuhr+swQWYDeV8+pU6fijTfeQF5eHoYOHYqwsDDMmzcP+/fvx4cffmiKPJKNKFcIWJFwUWualYfS0CXM3+qnJqhbS1wPMbHpNNlxOkPnJGXCv+mebx9q0D7cnMX1bBebTpNAb3dJ05H9Gz/+TcyaNQ35+fl4+ulBaNSoMVauXILDhw9hw4aPLJ09sqD8EnE998SmIyL7pymmHDnyC+soRlJOt1xyPZ/TjJFkrucWSZrOEXDNHfNgPJGW/K7IRkmR6YiqKi7TPQpUn3REtkZU486aNWvw4osvwtvbGw0bNsQff/yBgoIC+PhUrAPy2muvIT4+Hq6uHDLtyBIz8rSuHQMAWQUlSMzIs/ph4mJnTzB2loXTGbp7pivTGdq4kyPyJklsOk3MsX5QZba+rpOj2rTpIzz77PPw8vJCcHAo9uzZj8LCQtSpUzE3+MiRL+P11yfjgQfYS9ORZYnscSo2HRHZJ10x5cUXX8a8ebNZRzGCPUy3TNbpgohe1vqkcwTmrm85EsYT0/nr6h3R6UZ0eNDEuSG7ZK4HeERWStQ8T5s2bUJeXsVD6P/973/Izc1VNewAQEBAAIMc2dUwcXM1iNRyFTfVmth0NblTdF/SdJo4O8nQs0Wg1jQ9mteTpAEmIVWOfh8fw9jtyZj5QwrGbk9Gv4+PISFVbvRnk2l99dVnKCjIBwAMHtwPeXl5qkoTANSt6w8XFw7Jd3T3y8X1qhKbjojsk5iYwjqK4ZTTLVd9kKycbpn3XWSMUpExXGw6R+DsJMPkuKZa00zqFsYObwZgPDGd/CKRI/JFpiOqSiYTd80Tm47I1oh6gtaoUSNMmDABLVq0gCAIWLBgAdzda55aafHixZJmkGyHuaYyq8xU00SYq0EkrJ4XkKK7YhxWz8vgffh5iitvsek0KVcI2JdyS2uan89nY1znxkZ9R/ayrpOjCg1tiBkzpqBp03AIgoDVq5dViycyGeDu7sp44sBquTgjDwpR6YjIcemKKcp4ArCOoi97mm6ZrFNtVxfkFevuKFfblZ1+yPQYT0zH1UVcjBCbjqiq8MDakqYjsjWihgOsXbsW7du3V/1bEDiWjaoz90jIhFQ5+mz4E2O3J+P1rYkYuz0ZfTb8KUkvQnM1iBSIXC9CbLqaBNQWOTezyHSa6DMtn6HEPmgoV/AaZa0WLlyKqKh2lV6p/l0xxJDY3zB/60SOTVdMYTwxnDnu68ixuTqLfOArMp0jYF3IdBhPTKdZgLiOqmLTEVX1q8hngGLTEdkaUd1gHnzwQUyfPl317xkzZsDLixdeUnfnnsjRLiLTaaNp9Ib87n1JRm/4iRxdJDadJrcKSiRNVxNzNbqZY1o+e1rXyVEFB4dg4sTJqn+/8cZbqFVLvQeNTAYEBHibO2tkRe7eFzcFi9h0RGSfdMUUxhPD2dN0y2SdSkQubC02nSNgXch0GE9MJ9jXQ9J0RFWdF7k2m9h0RLZG7zHOAwYMwLlz5zRurzzChxyLuaZlK1cIeOf7FK1p3vk+BV0mPmrwNBFpIi/6adl38VCjugbtAwACvESOqhGZribmanQzx/fPBw32pXfvvrhw4Xy112UywMenFuOJAxM7QpgjiYlIqaaYoownAOso+jLHPaq9MtW00fZGoXv2Vb3SOQLWhcyD8URaXF+LTE3sUjpccofsld6NO8OGDavxdTc3N9SrVw8HDx40OlNkm8w1QuTY1dsoLdd+l19arsCxq7fxSGN/g/Zx9c49SdNpcq9E3A2M2HQ1MVfl3BzfPx802JcJE8bU+LqrqxsCAxlPHJnYmSiNmLGSiOyMppjCOophooJ9EOjlpnWUQJC3O6KCfcyYK+uXkCrHioSLauUW6OWGyXFNuSZkFbkiF08Xm84RsC5kHown0tqZnCk63csPNzZxbsgeNfWvhVuFuqeJbepfywy5ITI/vRt3UlLUR0yUl5fj2rVrmD9/Pvr27StZxsj2mGuEyJcnMkSnM7RxJ+mGuPnDxabTRCay64DYdDUxV+XcHN8/HzTYlyNHjqv9u7y8HBkZ17Fq1VIMHPi0hXJF1kBsczb79xGRUk0x5caN61i3biXrKAZwdpJhclzTGqdBVprULYwjUirRNG30rcJSSaaNtjelInt8iU3nCFgXMg/GE2ndvieugVZsOqKqdHX+1jcdka1xMvYDnJ2d0bhxY0ybNg3vvfeeFHkiG2WunkQFxeKCvth0NblXKu6iLzadJqF+npKmq4mzkww9WwRqTdOjeT2jK+fm+P6VDxq04YMG2+Xs7IwHH2yIiRPfZDwhIiKjKGMK6yiGi2sWgCX9WiGwyr1bkLc7Gyqq4EL3ZA6sC1kG44lxxJ6OPG3JUIUin8uJTUdka4xu3FHKyclBfn6+Xu+5evUqRo0ahejoaHTt2hUbN25UbUtPT8fIkSMRFRWF3r1747ffflN779GjR9GnTx9ERkZi+PDhSE9PV9v+ySefoHPnzoiOjsb06dNRVFSk2lZSUoLp06cjNjYWnTp1wubNm9Xeq2vfVDNlTyJtpOhJ1Kq+l6TpauLqLO6nITadJoMiG0DXPYzs33SGKlcI2HXmptY0u8/cNLqyGVG/jqhjiahfx6j9xDULwLDYkGo3f04yYFhsCB802IE7d+7oHU8AxhR74iHy0io2HRE5LtZRjBPXLAC7X+mIDwe3xXvPReHDwW2x6+UOvN+qQp+F7qmCl8hlOMWmcxSsC1kO44lhGvp5SJqOqKoAkes6i01HZGv0npYtPj6+2mt3797F0aNH0atXL9Gfo1AoMHr0aEREROD//u//cPXqVUyaNAlBQUHo06cPxo0bh/DwcHz77bc4cOAAxo8fjx9++AENGjTAjRs3MG7cOEyYMAGdO3fG+vXr8dprr2H37t2QyWTYt28f1q1bh2XLlsHf3x/x8fFYtmwZZs2aBQBYunQpzpw5g08//RQ3btzA1KlT0aBBA/Tq1QuCIGjdN2lmrukbXn8sDN8maW+sUKYzVKcmfvj6lO65YTs18TN4H0q6mlSM7d93Kj0X+TpGMeUVl+FUei7aNzT8eJIy8kQdS1JGnlH7SUiV4/MT16u9rhCAz09cR5sGdVipsRGLFs2t9tq9e/dw4sQxveIJwJhib5rUdcdZeYmodEREQM0xpajoHk6c+It1FCM5O8kQ+6AvAgK8IZcXQODgk2q40L3+Hm3sg30XdDd2PdqYU4xVxrqQ6TGeSOvlRxri7d3nRaUjMoSHq7gef2LTEdkaSc5sX19fTJ06FXPmzBH9HrlcjpYtW2LOnDlo1KgRunTpgocffhgnT57En3/+ifT0dMybNw9hYWEYM2YMoqKi8O233wIAduzYgTZt2uCll15Cs2bNsHjxYmRkZOCvv/4CAHz22WcYMWIEunXrhrZt22Lu3Ln49ttvUVRUhHv37mHHjh2YMWMGWrdujccffxwvv/wyvvzySwDQuW/Szhw9iTzdnNElTPtaOl3C/OHp5mzwPvxri5s6TGw6Tb5JuiFpupocv5YraTpNTqSLe7/YdDXhlBf2z8fHB+PHv6FXPAEYU+zN1VxxD7/EpiMix1Snjg/rKGQWXOhef8euFkiazhGwLmQ5jCeG+/NyrqTpiKpKk9+TNB2RrdF75M7ixYsl2XFgYCBWr14NABAEAadOncLx48cxe/ZsJCUloVWrVqhVq5YqfUxMDBITEwEASUlJiI2NVW3z9PRE69atkZiYiNjYWPz9998YP368antUVBTu37+PlJQUCIKAsrIyREdHq332hx9+CIVCoXPfpJ25ehIt798ab+38B4fTcqpt6xLmj+X9Wxv1+RezxV30xabT5HpusaTpanKzQHfvd33SaSK2F6cxvT31mfIiJtTX8B2RWUyfPrvG12UywM1Nv4cfjCn2pahM3IVCbDoisn81xRSZDAgI8NbrcxhPyBBc6F5/BSLXPhCbzhGwLmQejCfSOnerUNJ0RFXlFd+XNB2RrdG7cUcQBBw8eBCpqakoLy9XvV5aWoqzZ8+qzSEqVlxcHG7cuIFu3bqhZ8+eWLRoEQID1ReA9/f3x82bFVNxZWdna9yen5+PkpISte0uLi7w9fXFzZs34eTkBD8/P7UHhwEBASgpKUFubq7Wz9aXzIoXhFPmTco8iu1J1LWpvySLPK54ujWKSsux5tdLuHn3Ph6o7YqJjzUxasSO0t375boT/ZvOmDIM8RU3r2yIr4fB+wn0FveQPNDbzahj8XIXV+5e7s4G70d+V+SUF3dLJT23TfF7sRRrOhZBEHDkyGFcvpyG8nJlxV3A/fv3cfnyRYPiCWCfMcWQ78uavmt9yWQQNSelTGbDxwfbzHtVPBbr5IjHoimmuLjIWEepxNBzwp7OKVNwcZbhrbimeFvL9NSTu4XBxZkFqOTiBJSLqHK5OPG8U7pVKK4z3q3CEpZZDRhPLPPMy9td3GNHb3cXnrcaMAZrJ7ZYZGAZasJzTD/GlpfU5ax34878+fPxzTffoFWrVkhOTkZ0dDSuXbsGuVyOIUOGGJSJNWvWQC6XY86cOVi8eDGKioqq9dp2c3NDaWnFg11t24uLi1X/rmm7IAg1bgMqGqh07Vsf/v769eywBCnz+EdajqieRJcK7uNhHdOqiVWuEDCgfUPcKihGoLcHGjzgI0nDkZuruIYKN1dnvXvwVPZq9+Z47/AlaBs57ySrSOfmYtgsiiEBXqLTGXMs6fniKhvp+SUG7yesgbjfYVgDX6OORRNb+E2LZQ3HMm/ePMnjCWCfMcWY78savmu9iR2QI+jfi9Ka2OR3owGPxTo50rGYIqYwnkj/fns2OMAbdep4YO6es8jM+2/UfX0fD8zu2wq92tS3YO6sj7MTABGNO85Oth3rpXRfli0ynRPLTAvGE/M+84pr+QD+uqZ7fa24lg/wvNWBMbhmRWXiRngWlSl4junAc0w/1lJeejfu/PDDD1i+fDl69OiBXr16Yc6cOWjcuDGmTZuG+/cNG+IWEREBACgpKcFbb72FgQMHoqioSC1NaWkpPDwqRjm4u7tXCzylpaWoU6cO3N3dVf+uut3T0xPl5eU1bgMADw8PuLu7Izc3V+O+9ZGTY70LjspkFSehlHlMu5ErOl0zH+Pnm064IMfyhItqDUqBXm54K64p4sKNm/qtuETcuVxcch9yuXHzQLcI9MLZLM1DkFsEeiE/967Bn+8qiAt0roLCqGO5I3KB2DuFpQbvp4m3K+p4uCC/uExjGh8PFzTxdjX6e6nMFL8XS7GmY/n+++8xa9Z8dO0ahyFDBuL116fgwQcbYuHCuQbHE8A+Y4oh35c1fdemJOVv3Vzs6bvhsVgnRzyWmmJKw4YNsWzZQtZRKjH0nLCnc8qUYh/wws5R7ZGYkYdimRM8BAWigis6n9livDIlkVUUCArbjPWmYK56nb1iPLHMM69aIidWqeXM37omjMHaCSLXGRMUAs8xDXiO6cfY8lK+Xyp6DwUoLCxEmzZtAADh4eFITk6Gi4sLxowZg8OHD4v+HLlcjgMHDqi91rRpU9y/fx/16tWDXC6vll45dDQoKKjG7fXq1YOvry/c3d3VtpeVlSE3Nxf16tVDUFAQ7ty5g7Ky/x4OZ2dnw8PDA3Xq1NH42VWHrYohCNb9J3UeA2qLXEi0tpvR+zp4QY63d5+tNlLoVmEp3t59FgcvyI36/Jy74m7acu7eN2o/JfcVOKelYQcAzmUVouS+wuB93Lkn7lju3DPuWKJC6ojaT1RIHaP2U1YuaP38++WCpOe18g+Q/jMt9Wctx3L37l00b94KggA0adIUZ8/+A2dnFwwbNlKveALYf0yx9e9a3z8nkXcnTk6Wz6ujfTc8Ftv5c7Rj0RRTWEdRx3PK9H9OMhliQn3xVFQwYkJ94SSTWTxP1vinzzw6ls6rtfwF1BJZ365lfH3bXv/EXMcYT8TjeWtd566j/jGeSFSOPMfMWl5S0rtxJzQ0FGfPVswl3KxZMyQnJ/97QAIKCsS3gF6/fh3jx49HVlaW6rUzZ86gbt26iImJwT///KMabgoAJ0+eRGRkJAAgMjISJ0+eVG0rKirC2bNnERkZCScnJ0RERKhtT0xMhIuLC1q0aIGWLVvCxcVFbbG4kydPIiIiAk5OToiMjNS6b9JMuZCoNlIsJFquELDo5wta0yz6+QLKRbbe18RfZEOV2HSabDt9XefsQ8K/6QyVX6R5lIsh6TQZHBWsM6bK/k1nqJPpubinYz2ke/fLcTI91+B9kPk0aBCM1NQUAEDjxk1w7tw//27RL54AjCn2xkXkDbrYdERk/zTFFNZRiKyTi8gJ58WmcwRia7cSPzNyOIwn0rqvEDfiTGw6oqpcnMUNDxObjsjW6N2489JLL2HKlCn44Ycf0Lt3b+zcuRPz58/HtGnT0K5dO9GfExERgdatW2P69Om4ePEiDh8+jGXLlmHs2LHo0KED6tevj/j4eKSmpmLDhg1ITk7GoEGDAAADBw7EqVOnsGHDBqSmpiI+Ph4hISHo2LEjAGDo0KHYtGkTDhw4gOTkZMyZMweDBw+Gp6cnPD090b9/f8yZMwfJyck4cOAANm/ejOHDhwOAzn2TZs5OMkyOa6o1zaRuYUaviXMyPRd5WqblAoC84jKjHvDrsyCbMQ6lynUn0iNdTRQim4TFptPEzcUJL8SGaE3zQmyIwWsHAcCp67mSpiPLeu65FzBv3js4ePBn/O9/PfDjj3uxatVSLFgwR694AjCm2JsiEXPw65OOiOxfTTFl5cqlrKOQ2ZUrBJy4lotdiRk4cS3XqA5n9qzwvrhyEZvOEegzIwMZjvFEWt//k6U7kR7piKoqKhVXKRSbjsjW6L3mzjPPPINGjRqhVq1aCAsLw7p167Bjxw60adMGEydOFP05zs7OeP/99zF//nw8++yz8PT0xLBhwzB8+HDIZDK8//77mDFjBgYMGICGDRti/fr1aNCgAQAgJCQEa9euxaJFi7B+/XpER0dj/fr1kP3bq+fJJ59ERkYGZs2ahdLSUvTo0QNTpkxR7Ts+Ph5z5szBiBEj4OXlhQkTJqBHjx5q+dK0b7K8E9dyRafr0NDPoH2IbX8ysp0KOXdLJE1Xk8IScSNyxKbTZmKXJgCAL06oj0iSoaJhR7ndUGLbn6Qe4kim0bdvf4SGPghPz1po1KgxFi1ajj17dqJFi1Z4++3Jen0WYwoRkWOrKabs3buTdRQyq4RUOZYfTEV2pSme69V2xVv/a4a4ZsatCWpvOApFfwE6ZsnQNx3VjPFEWn/fyJM0HVFVjCfk6GSCoN9j0Js3b+KBBx6o9np5eTk+//xzjBw5Uqq82Ty53HoXopLJgIAAb0nzWK4Q0O/jY9XWwaksyNsdu17uYNTondk/nMMP57J1puvdsh7m9m5p0D5mfn8W+1J0j5bp2SIAC55sZdA+AGDw5r9w+U6xznSN/Tyw/aUOBu1jyYFUfJOUqTPdoMj6mNq9mUH7qKq0TIFvkm4gp6Qc/u7OGBTZwKgRO0rHr97Ba9/8rTPd+4Mi0N7Ahr2amOL3YinWdCy3bmUhMDCo2usKRTl+/HEn40klhnxf1vRd66v9il9Fpz0++TET5sQ0bPm7qYrHYp0c8VhqiikyGeDnV4t1lEoMPSfs6ZwylYRUOabuPqtx+5J+rdjAU4m9x3pTMFd9214xnkhPTEzovu435JXonnLNx90JB8Z3kihn9oUxWLu4tb+hoFT3Oebt5oSECTzHasJzTD/Glpfy/VLR+2nr0KFDceXKFbXXTpw4gaeffhrr1q2TKl9kgxIz8rTeaAJAVkEJEjOM65FRz8td0nQ1aV7PS9J0mtSt7SppupoE+3hImk4MNxcnPB8bgnlPtcHzRk7FVllksI+odX0ijVzXiczjtddeRnr6NbXXkpIS8dJLLzCeODhzTY1pCZyuh8g0NMUU1lHIHMoVAhaaeE1Qe2PPsd5UzDUNuqNjPJGWh8hnAWLTEVUV4ifuWZbYdES2Ru+r5+OPP46hQ4fi7NmzyMnJwZQpUzB8+HC0bt0aP/30kynySDZCrqNhR990mtTxFDeboNh0NfGtJW4ou9h0mjiJXCBUbLqahAXUkjSdJf2dma9zKK3wbzqyfl26dMNrr72MCxdScOfObcyf/w4mThyD8PAWjCcOzl4f+CSkytHv42MYuz0Zr29NxNjtyej38TEkGLGuGhFVqCmmTJgwhnUUMotT6bnIF7Em6Ckj1gS1Ny4ig7jYdERSYTyRVp3/Z+/Ow6Kq/j+Av2fYFRQEJQUz911AULM0E8vcUjMztbQyLcukvra45pr5c81M0ywrM8t9rTQ1zHZLFNQMQzFlcQEVRNmZ+/uDmByY5czMnTvb+/U8Po/M/czcc89dzr3n3HOOn9iLqqJxRJXdKhCbZ0w0jsjZmF37PXnyZNxxxx0YOXIk1Go1GjZsiA0bNqBdu3a2SB85kVrVBHuhCMYZosREkn8KNg78efEGHm5TdZhCUZ4eYu2ronH6HEsX25Zj6TfQuWGwxeu5na2GZbuSJzb3kGgc2df48RNQu3YdxMWNhUqlxp13NsDKlWvQunUbWbuokvMx3anevDhHYGi4nis3izFx1ykO10NkJX1lyqpVa3DffZ3tnTRyA0cEG22OpOXIOnSwMysT7MQkGucOyjQSFsefMRqz5OBZdGsczN47VmB5Iq/CYrG5fUXjiCrLFRiSzZw4ImdjUdeGZ555BqGhoZgyZQpGjx7Nhh0CAJQJDjQoGmfIkfM5ssbpcyXP9Dw45sQZclnw+6Jx+mTeKJA1zpRlh1KxPiEdt4868e6hVDwRHY64bo2s+u3rgm9aiMaR/Q0d+iRq1w7FvHmzMHz4SLRq1cbeSSKSHStjiJTBMoXsRfTxhuPY/8cVX+SwNXOGQY+uH6hMolwUyxP5ZNwQezYXjSOqrKxMrKQQjSNyNkKNOy1atIBKz7BQkiQhLi5O57O//vpLnpSR0zmWLjaXzrH0XNx9Vy2L13NL8I0O0Th9TN00mxtniEZw3G3ROH2u3RK7SRKNM2bZoVSsO5Je5XONBO3n1jTwBAl21RaNI+V17drBYHny5psTdT5jeUKugpUxRLbBMoUcRU1fsXcmReOI9FFqGHR3xPLEdtiQS7ZWKtjFUzSOyNkI3V1+9tln2v9LkqS30CMSPSysPXyqe3vIGqePt6fYd0XjDMkSvPEWjdPHV3CgatE4Q4pLNVifULVh53brE9Ix9t67LB6irU6Aj6xxpLxly1Zp/2+oPFGpgJo1HX8OKCJRrIwhsg1TZQrLE1JKoOCw06JxRPoECR4/onH0H5YntqMCTM6bWxFHZIlCwZZB0TgiZyPUuNOxY0ft/wcNGoR58+ahefPmNksUOaf24YFYgzShOGt0uCsIyVn5QnGWqlvDBycu5gnFWaO4VOzNAdE4fUQbY61ttN2SlAlTHYw0Unnc8Ohwi9YRGVYTNXw9jU5YW9PXE5FhNS36fbK9qKho7f9HjXoSU6fOROPGTXRiVCpwzh1yKSH+3rLGEVE5U2UKyxNSSq6Re1NL4oj0EX1aYyW5+Vie2E6QrwrXCk3XZwT58sglIrKE2a/PX7lyBR4e1vVWINcUXT8QpjpkeKph9ZAzdzcQG9JNNE4ff8FeP6Jxhnh4iN3AiMbpU9tfrAFKNM6QtOtic/aIxhlSamKc1BKOo+o0rl7NhlptWS8uImcSGVYTdUw03IQG+LBhmsgKLFPInjh0MCnhWr7gcNuCcaQfyxN5VfMWu+6JxhFVxoZvcndmD/o7cOBAjB49Gv3790dYWBh8fHyqLCf3VFyqQamJevVSTXmcnxWNIpFhNU127VX9G2cppXq7tLzDH8fSTfcQanmHv8XruLOWWPdx0Th7OpqWg/wS4wdZfokGR9Ny0KGB5T23SBm9evXFq6+Ox0MP9cEdd9SFt3d55bdKBQQE+LE8IZfhoVbh1dgmmLjrlMGYCd0bw0PNRw4iS+krUyrKE4DPKGRbHDrYfB4AygTjqFwtweHWRONIP5Yn8vLzEmsoE40jqqyGjxq5RaZf8q3hw2OMXJPZjTvffPMN1Go1vvrqqyrLVCoVCzo3tuyHVOG4iQ80tXg9Jy7eMDlmq/RvnKW9hCRJbBg00ThD7rmrllDjzj13Wd4LaXBEPSz9PtVkY9jgiHoWrwMAWt3hDyQJxlnoSFqOcBwbdxxffPx+eHh44MCBb6ss8/BQszwhlxLbNAQjYsKxPiFdZwhLtQp4IjocsU1D7Jc4IhdgqExRq1V8RiGbq+ihecXI3GnsoalLpGHHnDh3IPrkySnDrcPyRF43isTOYtE4osoCvFXILRKLI3JFZjfuxMfH2yId5ALScgSH5RKMM0SJialvFovdWIjGGaLE+NweahX8vNRGe7z4eamtfmM8T/BmTDROH9GOUlZ2qCKFbN68S+/nHNOaXFF8SjbWHUmv8rlGAtYdSUebejXYwENkBX1lCssTUgp7aJISrgsOtyYaR/qxPJFXsanhXcyMI6osT/CSJxpH5Gws6pOWl5eH9evXY+7cubh27RoOHjyItLQ0udNGTqZ+oJ+scYYoMTH1xRuFssYZcvif67LG6ZOYkSs0lFliRq7F6wCUGWu8fXigrHFkfzdv3sTWrZvw7ruLkZOTg59//hEZGVUrwImcWZlGwuL4M0Zjlhw8izIN37Ulsoa+MoXPKETkKpR4DqZyLE/kU2CiLsLcOKLKRKeotmIqayKHZnbjzt9//42ePXti69at+PLLL3Hr1i3s27cP/fv3x++//26LNJKTGNeloaxxhrQKFXtjRjROn+JSsQo20ThDMnPFejGJxumTLthTSjTOECXGGo+uH4hqJsbirealtng4Pn3KNBKOXMjBzsQMHLmQw8pXGaWmnsHQoY/gm292Y/v2zbh16yYOHYrHU08NZ3lCLiUxI9foUD0AcDmvyOpGdqXx+kiOxFCZwmcUUkKZRsKsPaeNxszac5rXSbKKEs/BxPJEbiVlYtc90TiiytSCg1GKxhE5G7Mbd9566y0MGzYM27Ztg5dX+Rv48+bNw/Dhw7FgwQLZE0jO4+SlG7LGGbI1KVPWOH1qVRecrFIwzhAlbnR2Hr8oa5whSj1seHkYv2yZWm6O+JRs9P/wMMZuOo6XNyRi7Kbj6P/hYcSnZMu2Dne2dOkiPPLIYKxZsw5eXuVvGE6ZMgODBg1meUIuRYnhRJXG6yM5GkNlCp9RSAl/XLiO/BLjQw/nl5ThjwuW98Yn2ib4fCsaR/qxPJEX54oiW8spEOv1JRpH5GzMrgU9ceKE3gnkhg4dijNnjA85Qq7tm1NXZI0z5Gi62JvNonH63CoWm+NGNM6Qat5ip6BonD4ZuWJDx4nGGbL9hFjjkGicPokZuSbnH8otLJXl7ff4lGxM3HWqytv2V24WY+KuU6zAlMFff51Cr159q3w+YMAglifkUlxtGBVXvD6yF5LzM1Sm8BmFlKDUcxC5t2OCzziicaQfyxN5iU41xinJyFKitXLW1d4ROS5Pc79Qq1YtnDt3DnfeeafO50ePHkVwcLBsCSPbKdNISMzIRVH6DfhoNIgMqynL5J75xcbfVjM3zpArN8UaIUTj9PESzA7ROENqV/dGTqHpdNaubnmFnySJVVCJxhmSdl1sWDfROH2UevtddH6Mbo2DOTGuFQIDg3DhwnmEhYXrfH7y5HGWJ+RSIsNqoo6/t9Gh2UIDfBAZVlPBVFnGFa+P8SnZWBx/Rmf/1PH3xquxTRDbNMSOKSNzGCpT+IxCSlDqOYjcm5/gC3+ice6kuFSDLUmZuFpUhmAfDwyOqAdvT/35xPJEXl4eQKlArbqXh+3TQkRkLXPKE6UINe6UlJRoh2AbM2YMpk2bhrFjx0KSJPz222/Yvn071q5di//97382TSxZz5YVGBH1AnDo7FWhOGt4qsQqi0Tj9LlWINamLxpniK+3FwDTjTvlcZbx81LjeqHpB0k/E3PZOAKl3n43Z34MOef3cQelpaXw9Cwvep54YiTmz38LI0Y8A0nS4OjRI9i792ts2vQFJkyYYOeUEsnHQ63Cq7FNMHHXKYMxE7o3dorGEFe7Plb0QqqsohfS/P6t2MDjwETKlM2bv+QzCtmcUs9B5N6ahvhjL0z3jm0a4q9AapzHskOpWJ+Qjts75b57KBVPRIcjrlsjACxPbEm0MzQ7TRORoxMpT+xBqHHn3nvvRa9evdCvXz8MHToUoaGh+Oijj+Dr64sFCxagYcOGmDNnDvr06WPr9JIVbF2B0TCkmqxxhpSUiY2TKRqnT0GRWKONaJwhXh5iFXmicfoE+HgBeSVicVZoU7cGtiSZHnKtTd0aFq+jbd0aUKuM3/ipVeVx1nDF+TEcxcMP90T37j3w4IO9MHDgo6hduw6++OIz+Pr6YsWKd3HnnQ0wceI0PP74IHsnlUhWsU1DML9/qyovWIT6+2BCbGOnaUBwpeujK/ZCcjciZQqfUUgJjWtXlzWOSJ/a/j6yxrmDZYdSse5IepXPNRK0n8d1a8TyxIZEOyyyYyMROTLR8sQehBp3pk2bhr1792L06NEICgpCnz59MHXqVLRq1crW6SOZKFGBsT85SziuSyPLK7FyC8QqjETj9MnOF2u0EY0zJEdw6DjROH1q+3vjdHa+UJw17qgh9hAhGqfPiYs3TL7Ro5HK46x5Y9zV5sdwJP/73+s4ePAAXn01DoGBgYiNfRAvv/wqmjVroY2xotMdkcOrPASmRnKuiT1d6froar2Q3JGpMkWlAkJC2FPCWrYa0tmVHE0TnBM0LRf3NOSwTmSZOgFiz1Gica6uuFSD9QlVK+Jutz4hHWPvvYvliQ2Jdshhxx0iclTmlCf2GKJNqHGnf//+6N+/P27evIkDBw5g7969ePzxx1G/fn3069cPDz/8MOrXr2/rtJIVlKjAuCX4qoVonCEFJWIVYaJx9pR+Q6wBSjROHx9PscFrReMMUWJOCaXeGHel+TEcTc+evdGzZ2/k59/CDz98j4MHD2Ds2FGoVy8MDzzwEB58sBfCw8NN/xCRkzHUezbrVolTDf/lStdHV+qF5K5MlSk9e/ZCSEhLeyfTqXFOKjGnLt2QNY5IH1cqg5WwJSlT6MXALUmZGM7yhIiIDDCrPIlWvj7LrOYkf39/DBw4EKtWrcKvv/6KMWPGICkpCX379sVjjz2Gzz77zFbpJCspUYERJXgTKRpniASxNwVF4/QJ9BNr6BCNM0S0/cmadqpTl/NkjTPEQ61Cy1DjbzO1qONv1ZueSr0xXjE/hjHOMj+Go6pWrTp69eqL+fPfwe7d+/DEE0/h1KmTGDHicYwZ8xTLEyuVaSQcuZCDnYkZOHIhB2UcxNquRHvPOsN+8lCr8FCLOkZjejav7RTXR1fqheTuDJUpTz75OJ9RrFDRKF25IrliSOf4FNNzf7iLa/mmh0A2J45IHz6jmCc9R2z0i9vjWJ4QEVFllpQnSrK4r5C/vz8eeeQRfPDBB1i9ejVKS0sxb948OdNGMqpVTWw+FdE4fR6LCjPZnKL6N84aPl5ih61onD6R4WKTUIrGGSJ6223N7XmJRnCOIsE4Q4pLNfjBxESyP5y9iuJSy9dT8baaMXK9rVYxP0bl9YUG+DjNG/bOonp1f/Tu3Q8LFizFokXvsjyxUnxKNvp/eBhjNx3HyxsSMXbTcfT/8DAr4ezInN6zjq5MI+Hb5CtGY/adznKKhiolyxRSDssUebhSo7QS/H2EBsQQjiMi64UH+loVx/JEHqJXPV4dichRWVue2JpF109JkvDHH39g3759OHDgAPLz8/HAAw/g9ddflzt9JBMlxjn19lTjyZhwvRNMVXgyJtzq8Qdr+Xkj+5bpuW5q+Vn+pu2v58Qq2ETjDPHzVOFWqelc9/O0vHmnoEhsXiDROEM2HcswefxI/8Y92cGyYRwr3lbTN7RRBTnfVottGoIuDWthS1ImrhaVIdjHA4Mj6tllDE1XJUkSEhOP4tChePzww/coKChAt273Y/LkSfZOmlMyNPRXxVvWbJi0D1ca/suV5qlRukwh29NXpvTs+SCfUSzgSue6Ero2roWkTNO94Ls2rqVAashVKTGPrisZHFEP7x5KNTqUjlpVHlcZyxP5iNYyWFcbQURkO9aUJ0oQbtwpLS3FL7/8gv379+O7775Dfn4+unXrhmnTpuG+++6DtzeHrHBk1wWHABCNM6RNvRpWLRcR0yAQf2fnC8VZ6pZgNojGGdIgyBensgqE4ixVJDjFkWicIUmZYg1dSZm5eBKWz9FV0aOm8vjvoQE+mNC9sawV1/rGmV9/JJ3jzFuptLQUR478jkOHDuKnnw6hoCAfnTt3wSuvvI7One+Ft7cXJyy1AB/4HZcrDf/lSg1VgLJlCtmGsTLlnnvuRd26rEy3hKud67bWtLZYb37ROCJ92OhqHm9PNZ6INv7y6RPR/718yvKEiIj0Mbc8UZpQ487rr7+OQ4cOIT8/H507d8Ybb7yBBx98ENWrV7d1+kgmSlQslWkkzN33t9GYt/f9bXXFYn6xWCuEaJw9+XiJzdkjGqePl4cKpQK9g7w8rKvs9RNMo2icMbf3qEnPKUR4oK/sPWrYA8I25sx5E7/88jMKCvIRE9MR48a9jPvu645q1arZO2lOjw/8jsuVJkB2pYaqCrFNQ9CtcTASM3JRpFbDR6NBZFhNNoI6AVNlioq70GKueK7b0rF0sZecjqXn4p6GwTZODbkqNrqaL65bIwDA+oR0nTeu1aryiriK5SxPiIjIGNHyxB6EGncyMzPxyiuvoFevXqhVi28rOKPIsJqo5qVGfonh+U6qeamtqlg6mpaDG4XGO9PmFpbiaFoOOjQIsng9Z7JuyRqnjxqAyMww1jYlpF413WvHnDh97gr2w1+XTfd0uivYz+J1AEDvlnWw568soThr2bpHDXtA2M6lS5fw3HMvonv3BxAYGGjv5LiUK3lFssaRfFxp+C9Xaqi6nYdahZg7AxESEoDs7DxInEbEKbBMsR1XPddt5eINsQl0ReOI9FFiHl1XFNetEcbee5fRobZZnhARkSki5Yk9CK19/fr1GD58uOwNO5cvX0ZcXBw6duyIrl27Yt68eSgqKq90SktLw9NPP43IyEj06dMHP/30k853f/nlF/Tr1w8REREYOXIk0tLSdJZ/+umn6Nq1K6KiojBlyhQUFPxXOV5UVIQpU6YgJiYGXbp0wccff6zzXVPrdkZlGgkFRhp2AKCgRGPVpKi//nNN1jhDMnLEGjpE4/QRadgxJ86QUsH8Fo3Tp5pgTxnROENUgq8zicYZUtGjpnJlQ0WPGjkmjXelyc8dzYoVH+KRRwbL/tDE8gS4XiA4/KZgHMmrYvivOpXecg8N8HGqnoAVDVXGOEtDFTk/lim2K1N4rpsn+6bYixOicUT6KDGPrqvy9lTjiZhwzB7QBk/omQeY5Ynz13kRESnBQ61C8zr+iG4QhOZ1/B3iXthuTUuSJCEuLg4FBQVYv3493nnnHRw8eBBLly6FJEkYN24cQkJCsHXrVgwYMAAvvfQSMjMzAZT3JBo3bhwGDRqELVu2oFatWnjxxRch/fua5bfffovly5dj9uzZWLt2LZKSkrBw4ULtuhcsWICTJ09i7dq1mDFjBpYvX469e/dq02Vs3c5qS1Km0GT3W5Is384/LuTIGmdIYanYcGuicfbk7yN2CorG6XOrWKwJSjTOENGGDmsaRER71FjTSAlwyANnw/KkXJCf2FuaonEkv9imIdg1phNWDWmHd4dGYtWQdtg5uqPTNOxUcJWGKiJ9WKb8h+e6uMxcsUYb0TgifZSaR5fkwfKEiMi1xKdko/+HhzF203G8vCERYzcdR/8PD8vykrk1hIZls4XU1FQkJibi559/RkhI+YNBXFwc5s+fj/vuuw9paWnYsGEDqlWrhsaNG+PXX3/F1q1bMX78eGzevBlt2rTBqFGjAADz5s3Dvffei99//x2dOnXCZ599hqeeegrdu3cHAMyaNQvPPvssXn/9dUiShM2bN+PDDz9E69at0bp1a6SkpGD9+vXo1asXfvvtN6PrdlbpOWJDAIjG6SMJjmEiGmdIec8P079hbQ8RJdSt4YPLN40PZVcRZ6ng6t4ATA9RVx5nudIywV5IgnH6KDWnCMeZdy4sT8rVCRC7TojGkW24yvBfnKeGXBXLFF0818V4Cs5dKRpHpE9NP7HqG9E4si2WJ0RErsOR5+W2W8+d2rVr46OPPtIWchVu3ryJpKQktGrVSmeC7ejoaCQmJgIAkpKSEBMTo13m5+eH1q1bIzExEWVlZThx4oTO8sjISJSUlCA5ORnJyckoLS1FVFSUzm8nJSVBo9GYXLezCg/0lTVOn9r+YhWGonGG+HiIDR8mGqeP6GOXtY9nV/LEen6IxulT3UvsNBeNM+RmselGKnPi9FGqR03FOPPGcJx5x8Hy5N+08bh1CmUaCUcu5GBnYgaOXMixuqehPVU0VA2IDEPMnYGs7CWXwDKlKp7rpt1Vq5rpIDPiiPT5+8pNWePItlieEBG5BqVGEbKU3V7pqFGjBrp27ar9W6PR4PPPP8fdd9+NrKws1KmjO+l6cHAwLl26BABGl9+4cQNFRUU6yz09PREYGIhLly5BrVYjKCgI3t7/VYCFhISgqKgIOTk5JtdtDkfqODKoXV28832qUJyl6W4YUg0/nbsuFGdN3gT4qHBdoINRgI/K4vWYM56xNduSdUusy3zWrRKL11MkODpdUZl122LOnDuWrsecHjXWbIunhwqvxTbBG0YmP3+1e2OnfPuyIl8c6fpUmblpY3nyb9pc+Lg1xpGP5cri/87GovgzOj0Q6/h747XYJoht5pzDGznDNUUUt8UxWbMtlnzH1csUS48JVzqmbKFb02D8mGr6Oahb02DmoQWYZ+VOXLwhHMc8q4rliePXefG41Y9lsHyYh/rxGDPOnFGEYu4MNPl7cuezw/TXXbhwIU6dOoUtW7bg008/1SmIAMDb2xvFxeUZWVBQYHB5YWGh9m99yyVJ0rsMAIqLi43+trmCgwPM/o6t/Hr2qlBcekEZOtcLtGgdeSViTSJ5JRJCQizPG41gfxkNVFatR5Q16ygTnOamTGP5ejo3CcEhgf3fuUmIVdvSMiwQSLwoFGfpeh6s5Y+63/6NS7mFehvgVADuqOmLByPDrX6rdEhIAGrU8MWs3adwMfe/1sS6NX0x4+FW6NWmrlW/b2+OdH2SmzuXJ65+3OqjxHVeDntPXsTEXaeqXLuy/u3GvfLJ9k69f1zpmsJtcUz22hZXK1OszUdXOqbkpFGLPVZr1J5OU245EuZZuUB/sVE2Av19mWdGsDxx3DovHrfGsQy2Ho8x43iM6VeULvZyRZFabZdjzCEadxYuXIi1a9finXfeQbNmzeDj44OcnBydmOLiYvj6lt/M+Pj4VCl4iouLUaNGDfj4+Gj/rrzcz88PZWVlepcBgK+vr8l1m+PqVccZS/9sZo5wXNOals0jEugjNqxXoI8a2dl5Fq0DAC7lit10XMottmo9oqxZh+D0QVCpLF/PzXyxeZRu5hdatS29mwZjrgow1gtRrSqPs2Y9/+vWyGDPBOnf5devyTMUQcwd/tjxbAckZuSiUKWGr/TfOPNKHFu2oFKVF9iOdH2qrCKNlmB54prHrTHOsE1lGgnTd5zUe7mv+GzGzj8RVae60w135AzXFFHcFsdkzbZYU54ArlmmWHpMuNIxZQtH/xF7ke7oP1eR3bqO6UDS4QxlvRIeaFwLOxJNT3r/QONazDM9WJ44fp0Xj1v9WAbLh8eYfjzGjPPRiL2Z76PRCB1j1pYpldm9cWfOnDn48ssvsXDhQjz00EMAgNDQUJw5ozuWXXZ2trbraGhoKLKzs6ssb9myJQIDA+Hj44Ps7Gw0btwYAFBaWoqcnBzUrl0bkiTh+vXrKC0thadn+eZnZWXB19cXNWrUMLluc0gSHOakCKkuOJxVdW+L09yxfhA+PZwuFGdNvojO2FIKZfLfmnX4eAD5Ahvk42H5ek5eFCu8Tl607iLu5aHGE9HhWHfE8DHwRHQ4vDzUVq2ne9MQzO/fCosrDW0U6u+DCbGN0b1piKz7Xa1SIbq+7uTnjnJeW8NVtuN2LE/+46rHrT7OsF3H0sW6cR9Lz0V0/UBlEiUzVzrGuC2OSeltcdUyxdp8dKVjSk4FxWIP/QXFGuafBZhn5aLCA4XjmGeGsTxx3DovHrfGsQy2HvPPOB5j+lXMb2zsmb5ifmN75J91M6hbafny5diwYQOWLFmCvn37aj+PiIjAn3/+qe1uCgAJCQmIiIjQLk9ISNAuKygowKlTpxAREQG1Wo22bdvqLE9MTISnpydatGiBli1bwtPTU2eyuISEBLRt2xZqtdrkup1VZFhN1PQ13pZX09fTqom2m9X2lzXOHagEh2UTjdPHz8tD1jhj4ro1QrfGwXqXdWscjLhujaxeRwWp0hVTI1mRSeT0WJ7oKtNIOHIhBzsTM3DkQo7dJvajctkmGnbMjSP58Zyh27FMIXO1qSf2fCMaR6SPOXPukGNgeUJE5Pw81Cq8GtvEaMyE7o3tNgqH3Rp3zp49i/fffx9jxoxBdHQ0srKytP86duyIunXrYvLkyUhJScHq1atx/PhxDB48GADw6KOP4ujRo1i9ejVSUlIwefJkhIeHo1OnTgCA4cOHY82aNThw4ACOHz+OmTNnYsiQIfDz84Ofnx8GDhyImTNn4vjx4zhw4AA+/vhjjBw5EgBMrtuZ2bqaYva+07LGuYNCwZ0iGqdP75Zib+CIxhkTn5JtcH6fQ2evIj4lW+8yc9cxcdcpZN0q0fk861YJJu46Jcs6yLmwPNEVn5KNh1f/hrGbjuPlDYkYu+k4Hl79G88NOwrxF+w9KxhH8opPyUb/Dw/rnDP9PzzMc8ZNsUwhi2gEH+ZF44j04MsizoXlCRGR64j9dxShOpWe2UMDfDC/fyvENg2xU8rsOCzbd999h7KyMqxcuRIrV67UWXb69Gm8//77mDp1KgYNGoQGDRpgxYoVqFevHgAgPDwc7733Ht5++22sWLECUVFRWLFiBVSq8pvlvn37IiMjA9OnT0dxcTF69uyJ119/Xfv7kydPxsyZM/HUU0/B398f48ePR8+ePQEAHh4eRtftrBIzcnGj0Pj4X7mFpUjMsHxImPScAlnj3EGZYKONaJw+FeeFXHGGlGkkLI4/YzRmycGz6NY42OLWbCXWYQ9lGgmJGbnIvlmMEH9v7fwoJIblyX8qGj8rq2j8tPdNh7uq6D2ba6Qctrb3LFnG0Dlz5WYxzxk3xTKFLPHjObE5d348dxVP332njVNDroovizgXlidERK4ltmkIujUORmJGLorUavhoNA5Rf6eSKo9tRLKpmOfAEXz95yXM3Pu3ybiZvZqhb+s7LFrHs18cxfGLpieyb1fXH2uGt7doHQDQafEPEBmASw3g8Kv3WbSODot/EI79w8J1KLWeFT+m4tPfTc+F9HTHcIzravmwaQlpORi76bjJuFVD2lncgKjEOvRRqaAzd4mc4lOyq8wfVMffG6/GNrFJhaItt0UuFWmk/4jsrzKNhJ4rfzXakF/T1xPfvtDZ7jcfpih1DVaKK+2bypzhmmJImUZC/w8Pmxw7eefojtwvdmTNtrA8qcrSY8KVjilbGPLx7zh3vdBkXMMgX2wa1VGBFDk+VyvrlVBQXIb73vvZZNwP4++Fn7f1Q267GpYn8hPJS57r1mMZbByPMevxGDOPtfkld5li1zl3SDknMgXH5xWM06d1PbEDUzTOENGZVTgDS7k/BcdcFo0zRIlhAuwxFEFxqQbrj6Rj+s6TWH8kHcWl8h1ZFW+MV65YrHhjXO4hgTinhGs7mpYj1EPzaFqOMgkiLXN6zzoTZ7+mJGbkGm3YAYDLeUVOt1+ISHmegk/VonFE+mw/cVHWOCIiIjKPIz4D221YNlJW9i3BSnHBOH3OXLklaxzJo0iwMUI0zhAlhglQeiiCZYdSsT4hHbdfq989lIonosMR183yXk6A8kPMKd1DiJR3RLDR5khaDjo0CLJtYkiHK46RH5+SjUXfpejMf1a7uhde69HUaa4prrhfiMg+8orLZI0j0ic9x3TvMHPiiIiISJyj1qvx3SE3UU2wW7ZonD5KNCCR+bw9xE5z0ThDKuaUMMbaOSUiw2pWmbysstAAH1nmrVh2KBXrjug27ACARgLWHUnHskOpVv2+km+MK91DiOxDdNosK6fXIgu42hj5FdeU2xt2gP/mdnKWa4qr7Rcisp8ywXekROOI9KlbQ6w8Eo0jIiIiMY5cr8bGHTfRt1WorHH6qAVrDEXj7Ek0hdZuiZfgD4jG6SfaRdD6roS27ozooVbh1dgmRmMmdG9sdU+X4lINPj9ifJ6iz60cok2pN8ZFewg5QldSsk778EBZ40g+kWE1UcPGjd9KKdNImLvP+Bx+b+/72ymuKW3r1oCp4kKtKo8jIjImvKZYZbpoHJE+omWrM5TBREREzsLR69XYuOMmogQq81SCcYY0rOUna5w9KdUcEugr1lNKNE6fojKxVIrGGaLUnBKxTUMwIia8SoWcWgWMiAmXpSvk5mMZJvet9G+cpZR6Y5xzSriP6PqBQr3nousHKpMg0lFq4hpbYuU1WCmuNLfTiYs3qvTOrEwjlccRERnj6+UlaxyRPj+lXpM1joiIiExz9Ho1Nu64CZGKCUkwzpCbJWJjSIvGuQOVYA8T0Th9/DzFGoZE4wxRqidKfEq20eHS5OgKeUzwgiwap49SQ8wpPadEmUZCQloOvv3rChLSHGNyOXfhoVahf5s7jMb0b3OHLHM4kXkS0nKQb6Lsyy8pQ4ITNIiYM7eTo+OcO0Qkl5Ssm7LGEREREZFjcPTnRjbuuIkreUWyxulz6mKerHHuoKBEbFgv0Th9Wt4hNpyMaJwhSvREUaorZHXBuadE4/RRaog5JeeUiE/JRv8PD2PspuOY9k0yxm46jv4fHnaa+TecXZlGws6Tl4zG7Dp5iQ1udnA0PUfWOHtypbmdOOcOEckl10SPRnPjiPTp0qiWrHFERERkmqM/N7Jxx01cuyXWeigap09+sVgDhGicO1CicSe6vlijjWicIUr0RFGqK2RvwbmnROMMiW0agvn9W1XJt9AAH8zv30qWIeaU6iHkyJPLuQtXGi7L1UiC7WmicfbkSnM7KXV9JCI3oNwUl+TGWoQGyBpHREREpjn6cyMbd9zEtQLBxh3BOH1EX9J1gpd5FVMq+IAnGqfP2ex8WeMM8VCr8FCLOkZjejavbVVPFKW6Qna4MwjVvIxfHqt5qdHhziCr1gOUN/DsGtMJq4a0w1t9WmDVkHbYObqjLA07gDI9hBx9cjl38ceFHFnjSD6RYWKN56Jx9uRKczspUW4RkZvggxApILdAsIeYYBwRERGZptTIO5Zi446buCw43JponD6egsewaBzJI/OG2D4VjTOkTCPh2+QrRmP2nc6yqoJfqa6QHmoVZvRuYTRmRu8Wsl24PdQqRNcPxEMt6yC6fqDsBYKtewg5+uRy7uLijUJZ40g+Z7JvyRpnTx5qFab0bGY0ZkrPZk7RIKJEuUVE7sFT8KlaNI5In1rVvGSNIyIiIjEG69X85Rt5x1LGX70kl6HEsGwFgiOHicaRPMIDfWWNM8ScCn5L3+iu6AppbD1ydYWsuHAv+i4FWbdKtJ/Xqe6NV3s0seuF2xKxTUPQrXEwEjNyUaRWw0ejQWRYTVkqYB19cjl3IQmO6SUaR/I5nnlD1jh7q7g+Lo4/o3M9DvX3wYTYxk5zfVSi3CIi96ARfL4RjSPSp0zwHk40joiIiMxTuT5FI9n/5o6NO26iqFTsYBONI+fxSNu6eOf7VKE4ayhRwV/RFXLirlMGY+TsCmnLBhF78FCrEHNnIEJCApCdnSfb/B6OPrkckb35enrIGucIXOH6yIZpIpJLkeAjlGgckT7H0sV6wR9Lz8Xdd9WycWqIiIjcR8U805Vl3SrBxF2n7Np7hx3D3YSPYIWRaBw5j5MXxd4EF40zRKkKflsPMVZZRYPIgMgwxNwp/5BprsDRJ5dzFyqV2LEpGkfyaVy7mqxxjsLZr49smCYiImciQbCXtmAcERERmebo80yz546baBHqjz/STL/p0yLUX4HUUAU1AJEX+KxphTVnkvUODYIsXo/SQ6ZVvDGefbMYIf7eNntjvEwjlb+Znn7DKd9MV4LSPapIv9AAH1njSD43C8tkjXMUxaUabEnKxNWiMgT7eGBwRD14O9GEEkqWW0RERNYK8BGrvhGNIyIiItMcfThvlvoOpKIS2RaV1cHVxN46FY0jeYi26VrT9puZWyBrnCEeahUealEH646kG4zp2by2U1Xwx6dkV5lToo6/N16Ndb45d2zN4BwcAT6Y0N155uBwZgG+Yj0vReNIPlfyCmWNcwTLDqVifUI6bn856d1DqXgiOhxx3RrZL2FmcNWGab6UQETkmvIEXwIRjSMiIiLTruQVyRonNzbuOAhbVyIHVvOSNU4fJXqhuBpPNVAikGnWvAh9Lb9E1jhDyjQSdp68ZDRm18lLGNe1odWVTEo0uhgaT/PKzWK7j6fpqJTsUUVVpWTdkjWO5CM6xYKzTMWw7FCq3oZ8jQTt587SwFPRML3ouxRk3fqvHHTWhny+lEBE5LpER9blCLxERETyuXpLbA5W0Ti5sZ7dAVRUIlfu4lVRiRyfkm31OrIFDzDROH1crfJKCZJgZojG6ePnJXaai8YZcjQtBzcKS43G5BaW4mhajlXrUeJ8cfTxNB2Zh1qF6PqBeKhlHUTXd745OJxZRo7YWyKicUT6FJdq8LmRHpoA8PmRdBSXOllpX6kmzBmv7kqUj0REZD8xgkO9iMYRERGRaabqOs2Nkxsbd+xMqUrk3/65JmscyUOJYdnahwfKGmfI4fPXZY3TR6nzxZzxNIkcRW6BWOO8aBzJx5XetN18LMNkmST9G+cMKhpEsipd87OcrEGELyUQEbm+iLCaMHWroPo3joiIiOTh6M/zbNyxM6UqkS/niVXmicaR83gsKkzWOEP+unxT1jh9lDpfsk2sw9w4IiX4eYvNpSMaR/KpXd1H1jh7OiZ4fRWNs6cyjYS39/1tNObtfX87RYMIX0ogWyrTSDhyIQc7EzNw5EKOU5wTRK7oxMUbQi9YnLh4Q4nkEBERuQVH7znLOXfsTKlJmcpKxbqGicaRPNQqoEzg+diaka081Cp4e6hRXGZ4iBwfD7XVw2f5CE4MJBqnj1KNLiH+3rLGESnBx0PsHBaNI/ncKhYrW0Xj7Km6YOOgaJw9JaTlIFdgONGEtBx0bBCkUKosw5cSyFbiU7KrzElVu7oXXuvRlPM4ESmM13oiIiLlVfScNVZ9a8+es+y5Y2fXC8QmsReNM6RUEnvDTjSO5FEqmN2icfokpOUYbdgBgKIyDRKsnAunToBYQ4donD5KNbpEhtVEDV/jbd81fT0RySEPyIGYOmbNjSP5ZN0UK8NF4+ypd6tQWePs6Wh6jqxx9sSXEsgWtMMW3tK9NmXdKnGqYQuJXAWv9URERMpz9J6zbNyxs+reYrtANM6Q3MIyWeNIHkrMuXPkQo6scYa0DPWXNU4fJRtd2LeBnE2RYCuwaBzJp6BYrNFGNM6eOtwZhGpexu9Jqnmp0eFOx+7pAkB4aClnGIIqMqwm6piozAsN8OFLCSSsTCNhrosMW0jkKnitJyIiUp5So25Zio07dnbozFVZ4wwpFmyzEY0j53Epr1DWOEP+uiQ4545gnCFKNLokZuQKDdXDuQvIkSjRWEyWyRXsfSsaZ08eahUejahnNObRiHpWD/WphEBfL1nj7MlDrcKrsU2Mxkzo3tgp9gs5hqNpObghcC901Mqe30Qkjtd6IiIi5Sk16pal2LhjZ1mC4+GKxhnCSj/3dUcNsQm6ReMMyboleCwLxumjVKMLx7MmZ3Q9X/CGQzCO5JMj2CtWNM6eyjQSdp28ZDRm18lLTvE2f2A1wcYdwTh7i20agvn9W1V5qzs0wAfz+7fi/ChkliOCjTaicUQkD17riYiIlFVTcGh70Ti5ceB9O+McCWRrkfUCAaQLxlmuurfYMSoap49SjS4cz5qckSTYPC8aR/LxEHyVRjTOnhLScoQa2RPSctCxgWMPzeaKDaKxTUPQrXEwEjNyUaRWw0ejQWRYTb7FTWZTCR4yonFEJB9e64mIiJTDnjtkVIf6YhUfonHkXDxkjtMn9dotWeMM6dOqjqxx+ijV6MLxrMkZBQv2LhCNI/nU8BF8kUMwzp6OpF2XNc6eTA05ZW6co/BQqxBzZyAGRIYh5s5AVvaRRdqHB8oaR0Ty4rWeiIhIGTcKBJ8bBePk5hCNO8XFxejXrx8OHz6s/SwtLQ1PP/00IiMj0adPH/z000863/nll1/Qr18/REREYOTIkUhLS9NZ/umnn6Jr166IiorClClTUFBQoF1WVFSEKVOmICYmBl26dMHHH3+s811T65ZTfqnYjheNI+fiLdhqIxqnT0aO2Fw6onGGdLgzCN4mXjv38bBukm2lGl04nrXzcufyJNBPrFFTNI7kUztAbNhL0Th7yhQsK0Tj7El05DgnGGGObMSdy5To+oEmh5ao6euJ6PqBNksDEZGrcOfyhIjI2akFW09E4+Rm98adoqIiTJgwASkpKdrPJEnCuHHjEBISgq1bt2LAgAF46aWXkJmZCQDIzMzEuHHjMGjQIGzZsgW1atXCiy++CEkqf/r+9ttvsXz5csyePRtr165FUlISFi5cqP39BQsW4OTJk1i7di1mzJiB5cuXY+/evULrlptKcHp40TjD35c3juRRQ3CSZtE4e/P1Mn5JMbXcFA+1Ci1DA4zGtKjjL0ujC8ezdj7uXp78c1Ws951oHMlHLThukWicPV3LFxv2UjTOnm4WiXWbF40j1+LuZYqHWoUpPZsZjZnSsxlfdCEiMsHdyxMiImfn6D3a7dq4c+bMGQwZMgQXLlzQ+fy3335DWloaZs+ejcaNG+P5559HZGQktm7dCgDYvHkz2rRpg1GjRqFp06aYN28eMjIy8PvvvwMAPvvsMzz11FPo3r072rVrh1mzZmHr1q0oKChAfn4+Nm/ejKlTp6J169Z48MEHMXr0aKxfv15o3XKLEXzbTTSOnItaJfY6sGicPq3u8Jc1zpDEjFyTQ9fkFpYiMSPX4nUUl2rwY+pVozE/pl5FcanG4nXcLrZpCHaN6YRVQ9rh3aGRWDWkHXaO7siGHQfE8gS4IjjXlGgckT4FxWWyxtmTSrAxTTTOUZRpJBy5kIOdiRk4ciEHZex6ZDaWKeUMvujizxddiIhEsDwhInJ+jt6j3a6NO7///js6deqEjRs36nyelJSEVq1aoVq1atrPoqOjkZiYqF0eExOjXebn54fWrVsjMTERZWVlOHHihM7yyMhIlJSUIDk5GcnJySgtLUVUVJTObyclJUGj0Zhct9za1w9EDYEDpL2VB4inYL2EaBzJI69YrBFCNE4fpcaGvJJXJGucPluSMk0Oj6ORyuPkwvGsnQPLE0AteGyKxpF8qvuIja0pGmdPuYLzz4jG2VP9ID9Z4xxBfEo2+n94GGM3HcfLGxIxdtNx9P/wMOJTsu2dNKfCMuU/el90GcMXXYiIRLA8ISJyfo7eo92uM/cOHz5c7+dZWVmoU0d30vXg4GBcunTJ5PIbN26gqKhIZ7mnpycCAwNx6dIlqNVqBAUFwdv7vzfQQkJCUFRUhJycHJPrlpuHWoWpPZth4q5TBmPkOEBEW/HsPk6fmykuEWu0EY3TR6mKuOsFYsPWiMbpky44h4NoHLkOlidAk5BqOJKeJxRHymoa4o+9MF253jTEuh6UinChcV4HR9TDu4dSjb40oFaVxzmD+JRsvfeTV24WY+KuU+xpYQaWKUREJAeWJ0RErqGiR/ui+DPIum00lDr+3ng1toldn7Ps2rhjSEFBgU5BBADe3t4oLi42ubywsFD7t77lkiTpXQaUT3Jnat3mEB3Fo0ezECzo3woLv0tB1q3/Kr7r+HvjtdgmiG1m/QFSJDgiR5Eknm5rKDXCiaXr8VUBhQJ55quybltEB0qRYPl6VIItdiq1ddsSVE1sXqCgal4Wryc80Fc4Tq5jrEwjITE9F4XpN+AraRAZVtOpe+9U5IsjjzIkZ9rcqTzp3DBYqHGnc8Ngh97/5nKGbQmqLnh9rG759VEpd9TwQVqO6R6Yd9Twcfht8fFS44nocKw7km4w5onocPhYOV+cEso0EhbHnzEas+TgWdzfJNjpyjBryi25j0FXKFPMzZP4v7OxKP6MzpCecj6juCNHvzY6IuaZfs5wX+9IWJ7Yr87LXr/nKniuy4d5qB+PMTEqAJB0a3IlSYIK5uWd3PnskI07Pj4+yMnJ0fmsuLgYvr6+2uWVC57i4mLUqFEDPj4+2r8rL/fz80NZWZneZQDg6+trct3mCA42PvH77YaEBODRu+/C7+eu4UpeIeoE+KJjw1p2eQAPCRFPtyOvw5r1iDTsVMRZsy2eniqUlJhemaenyuL1dG0Wio9/SxOKs2ZbmoaJ3Qw2DQuyeD0vPNAcSw+lVr6W6lCpyuO8Pa2vjNt78iJm7T6Fi7n/9QSqW9MXMx5uhV5t6lr9+/ZkzvXJmblTeXLXHTWFfuuuO2oqdg1WgjNsy9nr5wTjCh1+e17s1gzPrDsiFOfo2wIAcwZHoFo1L3z44zmdHjxqFTCma0NM7tPKfokzw69nr5qcT+tyXhFS80rQuXGwQqmSlyOUW65QppiTj3tPXsTEXaeqvIyU9W9vsJVPtnf6+yF7cIZro6NhnhnnCNdHZ+II+eUK5Qkgf17yXDfOEY5dR+ShAsoE6vA8VDzGTOExZpih++LsWyV2vy92yMad0NBQnDmj+/Zhdna2tutoaGgosrOzqyxv2bIlAgMD4ePjg+zsbDRu3BgAUFpaipycHNSuXRuSJOH69esoLS2Fp2f55mdlZcHX1xc1atQwuW5zXL2aZ7QSWp+mNb3RtGb5WxTXr900e51yyM42/ea3M6xDqfVYs45qHmoUlJiedLqah9ri9exONN2wUxHXto7lwzU1CvBCHX9vo5VLoQE+aBTgZfG2lGkk+HqqUWBkmDo/TzWuX7tpdcNo/N/ZeEPP8DYXcwsx9vOjWNC/lVO+sapSlRfYllyflFKRRjm4U3mSniV2XqVn5Sl2DVaCM2zLhSti5fmFKzcdfnvybokNe5l3q9Dht6XCmI718VT7MGxJykR2YRlCfD0wOKIevD0tL3uVdjYzRziu4j7TWVhTbslZngCuUaaI5mOZRsL0HSf19jKv+GzGzj8RVae60/UGszdnua44EuaZfs5wX+9IWJ44Rp2XMTzX9eO5bpxIw05FHI8x/XiMGSf3fbHcZYpDjjMRERGBP//8U9vdFAASEhIQERGhXZ6QkKBdVlBQgFOnTiEiIgJqtRpt27bVWZ6YmAhPT0+0aNECLVu2hKenp85kcQkJCWjbti3UarXJdZtDkhznnxLpVipvlFiPOVMKWLMtKsG+eCqVyuJ1/HVZrFLxr8s3rdoWtUqFV2ObGF3HhO6NobZiW46l5xpt2AGA/BINjqXnWrUtpWUSFpkY3mbxwbMoLZOsWo+9/gH2T4NIGuXgTuVJkJ/g0F9+Xnbfv3Luf3unVeRf1i2xno1Zt4rtnlZT/745dVloW745ddnuaTXnn5eHGsOjwzF7QBsMjw6Hl4fa7mky519IdbEGm5Dq3nZPqyX/rDnX5eQKZYpovh1LzxXqDWbtPZer/LPFPnD1f8wz+fLR3mlwpn/W5JecXKE8AeTPN3sfH478j/ljPG94jMmTj/ZOg6P+s8V9sZwcsnGnY8eOqFu3LiZPnoyUlBSsXr0ax48fx+DBgwEAjz76KI4ePYrVq1cjJSUFkydPRnh4ODp16gSgfNK6NWvW4MCBAzh+/DhmzpyJIUOGwM/PD35+fhg4cCBmzpyJ48eP48CBA/j4448xcuRIoXXbUplGQkJaDr796woS0nJQZmyGX7IpL8HWHdE4Q3y9PWSN0yfAR6yDnmicMRUTjNXx161kCg3wkWUi52wTF1Nz4wxJzBC7cCdm5Fq1HrI9dypP6gT4yBpH8qntL5bnonH2dPGGWM8d0TiSR9u6NWDqJTG1qjyOLOdOZYpS91xERO7IncoTIiJndyXP9Jyz5sTJzSGHZfPw8MD777+PqVOnYtCgQWjQoAFWrFiBevXqAQDCw8Px3nvv4e2338aKFSsQFRWFFStWaHtB9O3bFxkZGZg+fTqKi4vRs2dPvP7669rfnzx5MmbOnImnnnoK/v7+GD9+PHr27Cm0bluJT8nGYj2Tlb4a28TqCnHg3x4mgnFkXrdOa6gEm2tF4/R5vH09/H7BdCPE4+3lOcZjm4agS8Na2JKUiatFZQj2+W94G2uF+Au+mSwYZwgrNFyHO5UnbevWMHmtV4GVu/YQHV4TP6ZeE4pzdHcE+CAJpoczuIONiIo6cfEGTL0TpJHK46LrByqSJlfkTmWKUvdcRETuyJ3KEyIiZ3e9oETWOLmpJEnuzkBUITtbbKzC+JRsTNQzt0cFOXo8dF78A0oF4jwB/PrqfRato8PiH4Rj/7BwHUqtp+PiH4Qbw363YlueWvcHTl0pMBnXqo4f1o7oYNE61v+RhqU/nDMZ98p9DfFEh/oWreN2tmyoLNNI6P/hYZPz+uwc3dGq8d8T0nIwdtNxk3GrhrRzukoy1b+TCIpen+yhIo30H5H99cf563hxywmTv/X+4Lbo0CBIppTZhlLliVIKistw33s/m4z7Yfy98LOip6YS1v1+Act+/MdkXFzXuzCi4522T5CMnOH6aMi3f13BtG+STca91acFHmpp/pj69mTNfmF5UpVoPip1z+UqXK3cUgLzzHrOXG7ZA8sT+YnkJc916/FcN+6+JT+gQCBf/FTADxN4jOnDY8y4PacuY/qe0ybjZvdujt6tQk3GyV2mOOSwbO6kTCPh7X1/G415e9/fVg/RVqu6WCct0ThXJ5rb1l7zygRPQdE4fTJuiHULFI0zpqKhsnJFwJWbxZi46xTiU7INfFOMh1psXh9rKxkiw2pWGVqustAAH0SGOf5b9uQ+jqTlyBpH8jmeKTaEo2icPYUIDh0nGkfyYC8LkptS91xERERE1vAUnC9BNI6oMkcfAp+NO3aWkJaD3ELjfWpyC0uRYGVlXK3qYhNti8bZk+g7zY797nM5bw+xU1A0Tp/wQF9Z4wxRqqHS1vP6AKzQIOckCTY3i8aRfHb/eUnWOHty9Btbd8WXEsgWlLjnIiIiIrKGaE8T9kghSzn6sxa7adjZkQs5wnEdrRhG54rgxMaicfZUJnOcPt5qoFgjFmeNejW8ceKiWJylBkfUw7uHUo2Oxa9WlcdZw5yGSmuOZaC8sqFb42AkZuQi+2YxQvy9ERlWU9bGlooKjcpDzIX6+2BCbGNWaJDDqeEj1jgvGkfyuSjYM1I0zp4iw2qihq8nbhi53tf09WQjgsIqXkowNswvX0ogS9x+z1WkVsNHo5H9nouIiIjIUsWCk2GLxhFV5ujPWuy5Y2eX88QaU0TjDLleKHYRE41zdbWqi71xLBpnSJPa/rLG6ePtqUbXRsFGY7o2Coa3p3WXg6PpObLGmeKhViG6fiAealkH0fUDbXYRrTwtmUYSaPUjsoOgamKNwKJxJB8fwd6XonH2xipdx8ReFmQrHmoVYu4MxIDIMMTcabt7LnIvokcRjzYiIjKmRLCKRjSOSB9HftZizx07C64uVskmGmeIUnPIuIpH29XFip//EYqzxpnsW7LG6VOmkfDX5TyjMclXbqJMI1n1sO5qXWEr5g+qLOtWCSbuOmX3izdRZbmFJbLGkXyah/rjjzTT8+k0D7W8IV8piRm5Qr00EzNyEV0/UJlEkRZ7WRCRs1BB7NmTVy8iIjKG9Z2kFEd91nKOV0Rd2M0i4xUk5saRPIbHhMsaZ8glwSF4ROP0SczI1RlWTJ/LeUVIzLBuIu8YwUo80Th7KtNIWBx/xmjMkoNnrZ4/iEhOQX5iw62JxpF8CorFBgoVjbOnK3li5ZFoHMmvTCPh9JWbSDh/Haf/fXmDiMjRBPiIVYSIxhERkXsSrdhmBTjJwRF7tLPnjp1dvWW80t3cOEMCfdTIKTLdBzHQx/Evd14qoESgnsLLivPL21ONETHhWHck3WDMiJhwq4cyq1fDB0mZxnvVVMRZKttEw465cYa0rx8oNA9Deydo3DGnQYxvppOj4ET3jkulEiuQROPs6XqBWM8v0TiS17JDqfj8SLrOm4lLv0/FkzHhiOvWyG7pIiKq7M6g6jhx6aZQHBERkSE+nkCBwPvwPqwBJxfl+DX5Lq6wVGzQR9E4Q8KD/GSN08dDsE5KNM4QXy+xw1Y0zpC4bo0wIiYclRth1aryhh05Kkn6tL5D1jh9QvzFhvQTjTPEQ63C1J7NjMZM6dlMtlbtMo2EhLQcfPvXFSSk5cj6ZrJSDWJEcmpbt0aV61VlalV5HCmrvmDZKhpnT67aQ6xMI+HIhRzsTMzAkQvylilKWXYoFesqNewA5UNQrDuSjmWHUu2RLKu4wn4hIv0GtBN7vhGNIyIi91TTV+y5QzSOyNmw3dLOWt0RgN8vmB4Oq9UdAVatp029Gjh5yfS8LW3qWV7p92DzEOxNzhaKs0Y1Lw/kFZtu7Krm5WHVeoDyBp6x996FLUmZSM8pRHigLwZH1LO6x06FDncGoZqXGvlGZnar5qVGhzuDLF5HZFhN1PH3NtoTJTTAB5FhNS1eR4WKCcYWfZeCrFv/vbVdx98br8Y2kW2OmviUbCyOP6OzTXKuQ6kGMSI5nbh4A6bqPTVSeRx7nClrcEQ9LP0+1eg4z6p/4xydK/YQs3WZooTiUg0+N9LbGAA+P5KOsffeJds9jK25wn4hIsPCA6vJGkdEjonza5GthQf64tJN06MGhAf6KpAaIuU5x9OdCxOttLemch8AUrMLZI3TJyxIrCJHNM6QAF+xNknROFO8PdUYHh2ON3o0wfBo64diu52HWoUZvVsYjZnRu4VVvV081Cq8GtvEaMyE7o1l61ET2zQEu5+7G6uGtMO7QyOxakg77BrTSdaGnYm7TlVprLpysxgTd51CfIrpBkZTKhrEjJGrQYxILq7U40x0eH1nGYbfQ62Cn4kXDvy8PBxivF5TXO36qESZooRNiRkmK06kf+OcgavsFyIyrFWo2MuLonFE5Jg4HwrZWivBkSlE44icDa+fdhYZVtPkGwqqf+Os4espVmEkGqfPNyezZI0zpEwSG5JDNM7eKnq71K6u20W0TnVvzO/fSpZGkYp1VK6QCw3wkW0dt7PVBGNlGgmL488YjVly8KzVw7Yo3SBGJAdX6nFWKngKi8bZW2JGLvJLyozG5JeUITHDdE9ee3Ol66NSZYoSEtNvyBpnT660X4jIsC1JYo3NonFE5JiM3wGbH0dUWVA1sedb0TgiZ8Nh2ezsxMUbQm9aWjuMTnB1sbElReP0uVUsVhyLxhmiEuywKxrnCGKbhqBb42AkZuSiSK2Gj0aDyLCaslaO3b6O7JvFCPH3ln0dtpaYkWt0eDkAuJxXhMSMXKuHnapoEKs8JExogA8mdG/MIWHI4VTMuWOsvtNp5txxsfEbXKlXFeA610clyxRbq+YtNhStaJw9udJ+ISLDfjhzVThuRIc7bZwaIiJyVsGCjTaicUTOho07dqZUhc8tgTlqzInTJzTABzeK8oXirNG0TnWkXjM9fFzTOtWtWo/SKnq7hIQEIDs7D7boeOShVjl1RYjSFaRKNLoRycWV5tzx8VAhX6Bbjo+Hc5yLrtSrqoIrXB+v5BXJGmdPfVrVwZ6/rgjFOTpXawwl9+CjBooEHqN8OG6GluijDvvoERGRMa44JyiROXh7aWdKVfhcEqyYEI3Tp1UdsckuReMM6df6DlnjyHnYo4LUVkPMEcnNlSpEA/3EepGKxtmbq81TU8HZr4/XC0xPvGpOnD21Dw8UGua3fXigAqmxjis2hpLr8xJ82UA0zh10axwsaxwROSYvwcueaBxRZa76rEUkio07dhYZVhM1fI13oKrp62n9nDuCDxKicfpcF3ldzYw4Q0QrJpyhAoPMw0KbyDBXqhCtVV0sjaJx9uZK89S4kiDBxkHROHsyZ5hfR8eynpyRWiV2/RaNcwePtw+XNY6IHJOvl1i1o2gcUWV81iJ3x6unA1Di8tIs1F/WOH2qe4uN8icaZ4hoxYQzVGCQeVhoExnmShWiYTXEGm1E4xxBxTw1lfdRaIAP5vdv5TTz1LgSVxrCwZV67rGsdzxlGglHLuRgZ2IGjlzIQZmpMUDdUK1qYs83onHuwNtTjRExxhtuRsSEw9uTVRZEzixY8LonGkekD5+1yJ3x6mlniRm5yC0sNRqTW1hq9aSxIdXEKiZE4/Tp1bK20HjvvVrWtngdgGtVYJD5XGUibyK5VVSITtx1ymCMs1SI+vmI9ZQQjXMUrjBPjSupaBC9YuR+wVkaRF2p5x7Ast6RxKdkV9kPdfy98WpsE+6H24QFVsM/OaafPcICrRue2tXEdWsEAPj8SLpO70MVgCdjwrXLich58fpISuGzFrkrNu7YmVINFUoMceOpFnurSjTOkKBqgsOoCMaR87m90M6+WYwQf28W2kRwnQrRq7fE5jgRjXMkFfPUhIQEIDs7DxJfgLcbV2oQdaWGqgp8QLe/+JRsvefHlZvFmLjrFN+EvY1a8PlGNM6dxHVrhLH33oUtSZm4WlSGYB8PDI6oxx47RC6C10dSEp+1yB2xccfOlHrTMkSw0UY0Tp/r+YITEwvGGSIJXp1F48g5eahVVvVmI3JVrlAhWlhivEeruXFEhrhKg6grNVTdjg/o9lOmkbA4/ozRmCUHz6Jb42CnO65sobCkTNY4d+PtqcYTMeE814lcEO/riYhsi407dqbUm5ZlgnfIonH6KNVQdTQ9Vziu0121rFoXEZEzcvYKUY3gfA6icUTGuEKDKOA6DVXkGBIzco0+nwDA5bwiq4eOdhVBfmKP1aJxRESugvf1RES2xbtLO1PqTctjgg0ix9JzcbeFDSJKNVSpBLNCNI6IiBxLqeCznWgckSnO3iBawVUaqsj+OMeleTjsEBGRfryvJyKyLd5dOoCKNy3rVOrREhrgI9tY1ko0iFQ0VBkjR0NV+/BAWeOIiMix1K3hK2sckTupaKgaEBmGmDsD2bBDFlGqR76rYLlFRKQfr49ERLbFnjsOwtYTxLcPD8QapAnFWUOJIUGi6weipq8ncgsNj8la09eTQ0QQETmpvq1DsTc5SyiOiIjkp1SPfFcRc2cgPvnd9LNWzJ2Btk8MEZED4X09EZFtsXHHgdhygnglG0Rim4agS8Na2JKUifScQoQH+mJwRD14e8rTUcxDrcKUns2MDmU3pWczvqlKROSkOtwZhGpeHsg3MvF0NS8PdLgzSMFUERG5D6WGjnYVfPmMiEg/3tcTEdkWh2VzExUNIsbI1SASn5KNR9b8jne+T8XmxEy8830qHlnzO+JTsq3+7QoGh7Lzl28oOyIisg8PtQozejc3GjOjd3NWKhIR2ZASQ0e7CiWftYiInAnv64mIbIs9d0hW8SnZet/wu3KzGBN3nZL1QZCTBhMRERER2Q7vt4mIiIiIHBd77riJMo2ExfFnjMYsOXgWZRrJoddRGScNJiJyPfYoT4iISD/eb5vGcouISD9eH4mIbIuNOwYUFRVhypQpiImJQZcuXfDxxx/bO0lWSczINTohKgBczitCYkauQ6+DiMjZuFp5ogSWJ0RE+rFMcUwst4jI2ShVnvD6SERkWxyWzYAFCxbg5MmTWLt2LTIzMzFx4kTUq1cPvXr1snfSLJJtojA1N85e6yAicjauVp4ogeUJEZF+LFMcE8stInI2SpUnvD4SEdkWG3f0yM/Px+bNm/Hhhx+idevWaN26NVJSUrB+/XqnfXAKqTQRqrVx9loHEZEzccXyRAksT4iIqmKZ4rhYbhGRM1GyPOH1kYjItjgsmx7JyckoLS1FVFSU9rPo6GgkJSVBo9HYMWWWiwyriTomCsvQAB9EhtV06HUQETkTVyxPlMDyhIioKpYpjovlFhE5EyXLE14fiYhsiz139MjKykJQUBC8vf8rgEJCQlBUVIScnBzUqlVL6HdUDjTXqKeHCq/FNsEbu04ZjHm1e2N4elieaCXWoU9FPjtSfluK2+KYuC3KcuS0mcue5Ykz7GtD7FWeKMWZ901l3BbHxG2x/DuOTI4yxdI8caVjyhZcvdxSAo8x8zHPzMPy5D9KPqPw+mg9nuvmYX6Zj3lmHmvzS+58ZuOOHgUFBTqFHADt38XF4uOABgcHyJouaw0JCUCNGr6YtfsULuYWaj+vW9MXMx5uhV5t6jrFOgxxtPy2BrfFMXFbyFyOUJ446762Z3miFGfdN/pwWxwTt8W1yFGmWJuP3A+GuUO5pQQeY+ZjnpmH+aX8Mwqvj/LgsWse5pf5mGfmcZT8YuOOHj4+PlUKtIq/fX19hX/n6tU8SJKsSbNazB3+2PFsByRm5KJQpYavpEFkWE14qFXIzs6TdR3H0nORfasYIdW9ERUu7zpup1KVn1COmN/m4rY4Jm6LsirS6ArsWZ44w742RYkyyx5cYd9U4LY4Jm6L7nddhRxliqXHhCsdU7bkquWWEniMmY95Zh6WJ/+xxzMKr4+W47luHuaX+Zhn5rE2v+QuU9i4o0doaCiuX7+O0tJSeHqWZ1FWVhZ8fX1Ro0YN4d+RJDjkSaFWqRBdPxAhIQHIzs6zSTor1nE7W+eFo+a3JbgtjonbQuZyhPLE2fe1EmWWvXBbHBO3xTG50rZYSo4yxdp85H4wzZXLLSUwv8zHPDMP88t+zyi8PlqH+WUe5pf5mGfmcZT8Uts7AY6oZcuW8PT0RGJiovazhIQEtG3bFmo1s4yIiMSwPCEiIrmwTCEiIjmwPCEich28auvh5+eHgQMHYubMmTh+/DgOHDiAjz/+GCNHjrR30oiIyImwPCEiIrmwTCEiIjmwPCEich0cls2AyZMnY+bMmXjqqafg7++P8ePHo2fPnvZOFhERORmWJ0REJBeWKUREJAeWJ0REroGNOwb4+flh/vz5mD9/vr2TQkRETozlCRERyYVlChERyYHlCRGRa2Djjg2pVPZOgWEVaXPkNIritjgmbotjcoZtceS02YsleeIM+1qUK20L4Frbw21xTNwWy7/j6izNE1c6ppTA/DIf88x8zDPzsDyRn7s/oyiFeWYe5pf5mGfmsTa/5M5nlSRJkrw/SURERERERERERERERLaitncCiIiIiIiIiIiIiIiISBwbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt3iIiIiIiIiIiIiIiInAgbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt3iIiIiIiIiIiIiIiInAgbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt33Nhzzz2HSZMm2TsZFisuLsasWbPQoUMH3HPPPViyZAkkSbJ3sixy8eJFPP/882jfvj1iY2Px6aef2jtJFikuLka/fv1w+PBh7WdpaWl4+umnERkZiT59+uCnn36yYwrF6duWxMREDB06FFFRUXjooYewefNmO6ZQnL5tqZCXl4euXbti27ZtdkgZmSs/Px9Lly5Fr1690K5dO3Tq1AlxcXFISUmx+rclScKoUaMUPxYmTZqE5s2bG/yn77h1NLbYLzdu3MDUqVNxzz334O6778akSZNw48YNGVMtpmI/ZGZmVln25Zdfonnz5njvvfcAlO/LivsKSZKwfv16RdNamSudL654jJWUlOC9995Djx490KZNG9x///2YN28ebt68afK7znJtcBVFRUWYMmUKYmJi0KVLF3z88cf2TpJTMHb/RbouX76MuLg4dOzYEV27dsW8efNQVFRk72Q5rPPnz+PZZ59FVFQU7r//fnz00Uf2TpLTcPY6EGdhTrlx6tQpPPbYY4iIiMCjjz6KkydPKphSx2FOnr3wwgtVnpkOHjyoYGodh0hZy2NMl0ie8Rgz797E3scYG3fc1Ndff41Dhw7ZOxlWeeutt/DLL79gzZo1WLx4MTZt2oSNGzfaO1kWeeWVV1CtWjVs27YNU6ZMwdKlS7F//357J8ssRUVFmDBhgk5FkyRJGDduHEJCQrB161YMGDAAL730kt5KQkeib1uysrIwZswYdOzYEdu3b0dcXBzmzJmD77//3n4JFaBvW263cOFCXLlyReFUkSVu3bqFYcOG4euvv8brr7+OPXv2YM2aNahevTqGDh2KtLQ0i39bo9Hgrbfews8//yxjisVMnToVP/30E3766SdMmTIFd9xxh/bvn376CVFRUYqnyRy22i8zZsxAcnIyVq9ejTVr1uDs2bOYNm2azKkX4+Xlhfj4+CqfHzhwACqVSvv31KlTMXXqVADAH3/8gdmzZyuWxspc6Xxx1WNs0aJF2LdvH9566y3s3bsX8+bNw88//4zXXntNsTSQmAULFuDkyZNYu3YtZsyYgeXLl2Pv3r32TpZDM3X/Rf+RJAlxcXEoKCjA+vXr8c477+DgwYNYunSpvZPmkDQaDZ577jkEBQVh+/btmDVrFlauXIndu3fbO2kOzxXqQJyFaLmRn5+P5557DjExMdi2bRuioqLw/PPPIz8/3w6pti9zytqzZ89i4cKFOs9M9957r8Iptj+RspbHmC7R+xN3P8bMuTdxhGOMjTtuKCcnBwsWLEDbtm3tnRSL5eTkYOvWrZgzZw7atWuHzp07Y9SoUUhKSrJ30syWm5uLxMREvPDCC7jrrrvwwAMPoGvXrvj111/tnTRhZ86cwZAhQ3DhwgWdz3/77TekpaVh9uzZaNy4MZ5//nlERkZi69atdkqpaYa25cCBAwgJCcGECRNw1113oW/fvhg4cKBDP0gZ2pYKR44cwW+//YbatWsrnDKyxIoVK3D16lVs3boVPXr0QFhYGNq0aYN58+ahbdu2Fvf4u3z5Mp566inEx8ejRo0a8iZaQEBAAGrXro3atWsjICAAHh4e2r9r164Nb29vxdNkDlvsl/z8fHz77beYPn062rRpg9atW2PKlCk4cOCAXd5kjomJqdK4c/PmTRw7dgytWrXSfhYQEICAgAAAsHtPWlc6X1z1GNu+fTtefvlldO7cGeHh4ejcuTNmzpyJgwcP8qUDB5Kfn4/Nmzdj6tSpaN26NR588EGMHj3a7j3zHJmp+y/SlZqaisTERMybNw9NmzZFTEwM4uLi8NVXX9k7aQ4pOzsbLVu2xMyZM3HXXXehW7du6Ny5MxISEuydNIfmCnUgzsKccuObb76Bj48P3njjDTRu3BhTp05F9erV3e4FAnPyrLi4GOnp6Wjbtq1TPTPJTbSs5TH2H9E84zFm3r2JIxxjbNxxQ/Pnz8eAAQPQpEkTeyfFYgkJCfD390fHjh21nz333HOYN2+eHVNlGV9fX/j5+WHbtm0oKSlBamoqjh49ipYtW9o7acJ+//13dOrUqUrPqaSkJLRq1QrVqlXTfhYdHY3ExESFUyjO0LZUdMOsTGT4GHsxtC1AeYH95ptvYvr06W5VSDsrjUaD7du345lnntFbobxgwQK8/vrrAMob7QYNGoR27drh4YcfxrfffquNqxg2q3///ujcuTP++ecf/Pnnn6hbty62bt2qrZh3FD179sQnn3yi89nDDz+MzZs3Y9u2bRg2bBgWLVqkHZZE6aESbbVf0tLSsGrVqirlQFlZGW7dumXbjdKjR48e+P3333Wud99//z1iYmJQvXp17WcV25Geno6RI0cCsM/wWaL7Zdu2bRg6dCjGjRuH6Oho7Nq1CxqNBh999BF69OiBdu3aYcSIETh9+rT2u0qfL7baFrVabfdjTKVS4bfffoNGo9F+FhUVha+//hpBQUHIz8/H9OnT0alTJ3Tq1AlvvvmmTsPTkSNH8PDDD6Nt27Z48sknkZGRoUi63U1ycjJKS0t1elFGR0cjKSlJZ9/Rf4zdf1FVtWvXxkcffYSQkBCdzx35Htue6tSpg6VLl8Lf3x+SJCEhIQF//PGHznMxVeUKdSDOwpxyIykpCdHR0dqe4CqVCu3bt3fo+gJbMCfPUlNToVKpUL9+faWT6VBEy1oeY/8RzTMeY+bdmzjCMcbGHTfz66+/4siRI3jxxRftnRSrpKWlISwsDDt27ECvXr3Qo0cPrFixwikfMn18fDB9+nRs3LgRERER6N27N+677z489thj9k6asOHDh2PKlCnw8/PT+TwrKwt16tTR+Sw4OBiXLl1SMnlmMbQt4eHhiIyM1P599epVfP311+jcubPCKRRnaFsAYNWqVWjVqhW6dOlih5SRuS5cuIBr164hJiZG7/I6derA19cXWVlZeP755zFo0CDs3r0bo0ePxqRJk3DkyBFt7M6dO/HKK6/ggw8+wF133YXY2FgsWLAAtWrVUmpzhPXt21enEeTs2bM4d+4cevbsCQA4ceIE/vrrL2zcuBEvvfQSZs2apei8XrbaL82bN8d9992n0/D62WefoXnz5nbZT82aNUNoaCh++OEH7Wf79+/HAw88oDe+bt262nl47DG0nuh+AYBjx46hSZMm2LRpE7p06YIVK1bg448/xpQpU7B9+3aEhYVh9OjR2m71Sp8vttoWX19fux9jI0eOxLp16xAbG4sZM2bg22+/RWFhIZo0aQIvLy9MmzYNCQkJeP/99/Hxxx8jISFBZyiEzZs3Y9q0adiyZQtyc3OxaNEiRdLtbrKyshAUFKRzrISEhKCoqAg5OTn2S5gDM3b/RVXVqFEDXbt21f6t0Wjw+eef4+6777ZjqpxDbGwshg8frp0PlPRzlToQZ2FOueGM9QW2YE6epaamwt/fH2+88Qa6dOmCwYMHu+Vwg6JlLY+x/4jmGY8x8+5NHOEYY+OOGykqKsKMGTMwffp0bUWAs8rPz8f58+exYcMGzJs3DxMnTsS6dessHmbF3s6ePYvu3btj48aNmDdvHvbu3Ytdu3bZO1lWKygoqNIrxNvbG8XFxXZKkTwKCwsxfvx4hISE4PHHH7d3csx25swZbNiwAZMnT7Z3UkjQ9evXAQA1a9bUfvbLL78gKipK+69v375Yv3497rnnHjz55JNo0KABBgwYgMcffxxr167Vfq9t27aIjY1Fu3btFN8Oc/Xr1w+JiYnaG6M9e/agS5cu2nxQqVRYsGABmjVrhsGDB6Nv377YtGmTYulTar98/vnn2LNnD9544w3bb5QBPXr00A7NVlxcjJ9//hk9evTQG+vh4aHNE3t04RfdL0D5MfTCCy+gcePGCAoKwueff46XX34ZPXr0QOPGjTFnzhx4eHjYrUxWalvscYyNGzcOCxcuxB133IFNmzYhLi4OXbt2xdatW5Gbm4u9e/di+vTpiI6ORuvWrTF79mzUq1dP+/0XXngBnTp1QvPmzTF48GAkJycrlnZ3YuheDoDT38+RY1q4cCFOnTqF//3vf/ZOisNbtmwZVq1ahb/++sspR7BQgivVgTgLc8oNV60vMJc5eZaamorCwkJ06dIFH330Ebp164YXXngBJ06cUCy9zoTHmPl4jFVl7N7EEY4xT8XWRHa3fPlytGnTRqf10Vl5enri5s2bWLx4McLCwgAAmZmZ+PLLLzFq1Cg7p848v/76K7Zs2YJDhw7B19cXbdu2xeXLl7Fy5Ur079/f3smzio+PT5U3TYqLi536xvrWrVt48cUX8c8//+CLL75wurcyJUnCtGnTEBcXV6WLKTmuiuGYbty4of0sKioKO3bsAADs27cPX375JVJTU3Hw4EGdnhIlJSVo2LCh9u+Ka6YzaNy4MZo3b469e/fi6aefxp49e/D8889rlzdo0ADBwcHav9u0aYMNGzYolj4l9sv69evx1ltvYfLkyXbtadejRw/ExcWhtLQUv/76K5o1a6aT945EdL8A5W9VVZRJV69eRU5ODiIiIrTf8/LyQps2bXD27FmFUq9LiW2x5zHWv39/9O/fH9evX8dPP/2Ezz//HFOnTkWTJk1QVlaG1q1ba2NjYmJ0ejDdeeed2v8HBATYZT4qd+Dj41Pl4bTib2e+nyPHtHDhQqxduxbvvPMOmjVrZu/kOLyK+WOKiorw2muv4Y033uBwy5W4Uh2IszCn3DAU627lizl59uKLL2LEiBHaF39atGiBP//8E5s2beKcUnrwGDMfjzFdpu5NHOEYY+OOG/n666+RnZ2trVyqOPi+/fZbHDt2zJ5JM1vt2rXh4+OjUxnWsGFDXLx40Y6psszJkyfRoEEDnRO/VatWWLVqlR1TJY/Q0FCcOXNG57Ps7OwqXRadxc2bNzF69GhcuHABa9euxV133WXvJJktMzMTx44dw+nTpzF//nwA5W8azJgxA9988w0++ugjO6eQ9GnQoAECAwNx7Ngxbc8OPz8/NGjQAAC0leylpaV4+OGHMXbsWJ3ve3r+V9z7+PgolGp59O3bF/v27UPXrl2Rnp6u01vk9u0CyucLUauV65Rs6/2yZs0aLFiwAG+88QaeeuopW22GkOjoaADlc94dOHAADz74oF3TY4zofgF0893QuVFWVma3YV9tvS32OsaSk5OxY8cOTJo0CQAQFBSEhx9+GA899BB69uyJP/74w+RvKHmuu7PQ0FBcv34dpaWl2mtWVlYWfH199c4DRWSpOXPm4Msvv8TChQs5xJgR2dnZSExM1BkatUmTJigpKcHNmzcdcphde3KlOhBnYU65ERoaiuzsbJ3PnLm+wFLm5Jlardbp0Q0AjRo1qlLvQuV4jJmPx9h/RO5NHOEY41ORG1m3bh12796NHTt2YMeOHYiNjUVsbKz27U9nEhERgaKiIpw7d077WWpqqlO9kV6hTp06OH/+vE5Lb2pqKsLDw+2YKnlERETgzz//RGFhofazhIQEnTeJnYVGo8FLL72E9PR0rFu3Dk2bNrV3kiwSGhqKffv2aa8DO3bsQJ06dRAXF4e5c+faO3lkgKenJx599FGsXbtW7yR+ly9fBlDeyH3+/Hk0aNBA+++7777D7t27lU6ybPr164ekpCTs2LED3bp1Q/Xq1bXLzp8/rzP5+8mTJxV909eW+2X79u1YsGABJk+ejGeffdZm2yDK09MT3bp1Q3x8PA4ePGhwvp0KFRNK2oPofqksICAAISEhOpNflpSU4M8//9TpZaUkW26LPY+xsrIyfPLJJzh16pTO597e3vD19YW3tzc8PDx0hlo7cOAAHnnkEUXTSUDLli3h6empcywlJCSgbdu2bGAj2SxfvhwbNmzAkiVLtENNkn7p6el46aWXdK7/J0+eRK1atdiwo4cr1YE4C3PKjYiICBw7dgySJAEoH2Xi6NGjTllfYA1z8mzSpElVhldPTk5Go0aNlEiq0+ExZj4eY+VE700c4RjjHbkbCQsL06lYql69OqpXr659+9OZNGrUCPfffz8mT56M5ORk/Pjjj1i9ejWGDRtm76SZLTY2Vjtx8Llz5xAfH49Vq1ZhxIgR9k6a1Tp27Ii6deti8uTJSElJwerVq3H8+HEMHjzY3kkz25YtW3D48GG89dZbqFGjBrKyspCVleV0kwl7enrqXAcaNGgAT09PBAcHIzQ01N7JIyPGjx+P2rVrY+jQodi7dy/S0tJw/PhxvPnmm1i2bBmio6MxfPhwnDx5Eu+88w7++ecf7N69G0uWLNGZp8LZ1KtXD+3atcPatWur3FTl5+djxowZOHv2LDZt2oS9e/di+PDhiqbPFvslJycHs2fPxiOPPIK+fftqrzdZWVkoKytTdPtu16NHD2zevBnBwcGoX7++0diKIStPnjxpl+GyRPaLPk8//TSWLVuG+Ph4nD17Fm+++SaKiorQp08fhbfgP7bYFnsfY61bt8b999+PF198Ebt370Z6ejoSExMxY8YMFBcXY9CgQRg4cCDmzp2L48eP48SJE3jnnXc4wbod+Pn5YeDAgZg5cyaOHz+OAwcO4OOPP8bIkSPtnTRyEWfPnsX777+PMWPGIDo6Wud6RFW1bdsWrVu3xpQpU3DmzBkcOnQICxcurNI7mMq5Uh2IszBVbmRlZWlf/uzVqxdu3LiBuXPn4syZM5g7dy4KCgrQu3dve26C4szJs9jYWG2D5fnz57F8+XIkJCTgySeftOcmOBQeY+bjMabL1L2Jox1jHJaNnNaiRYswZ84cDBs2DH5+fnjiiSecskEkICAAn376KebOnYvBgwejVq1aeOGFF/D444/bO2lW8/DwwPvvv4+pU6di0KBBaNCgAVasWOGUFc3ffvstNBqNznwfQHkD1rp16+yUKnInfn5+WLduHdauXYv3338f58+fh7e3N9q1a4f33ntP25Ni1apVWLRoEdasWYPQ0FBMmjTJ6efv6tOnD06fPo37779f5/O6deuidu3aGDx4MGrXro2FCxcarOi2FVvsl59//hn5+fnYvn07tm/frrPsu+++s1vPzi5duqC0tNRkrx0AaN68Oe69914MHToUS5YsQc+ePRVI4X9E9su2bduqfG/UqFG4efMm3nzzTdy8eRNRUVFYt26dXd+GtsW2fP3113Y/xpYuXYpVq1Zh+fLlyMzMRLVq1dClSxd8/vnn8Pf3x5QpUzB37lw888wz8PLyQp8+fTjBup1MnjwZM2fOxFNPPQV/f3+MHz9e8XOaXNd3332HsrIyrFy5EitXrtRZdvr0aTulynFVPF/NmTMHjz/+OPz8/DBixAg2uJJDMVZudOnSBfPmzcOgQYPg7++PDz74ADNmzMCmTZvQvHlzrF69GtWqVbPzFihPNM969uyJGTNmYOXKlcjMzETTpk3x0UcfucTIL3LhMWY+HmO6TN2bONoxppIq+g0REREROaB33nkHly5d0s4TBQDbtm3D8uXLER8fb8eUERERERERERHZB3vuEBERkUNKTk7GX3/9hS+++KLKGzNERERERERERO6Mc+4QERGRQzp58iRmzZqFxx57DDExMfZODhERERERERGRw+CwbERERERERERERERERE6EPXeIiIiIiIiIiIiIiIicCBt3iIiIiIiIiIiIiIiInAgbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt3yG1duXIFb775Jrp06YJ27dqhb9++WLNmDUpLSwEA27ZtQ2xsrGzrO3z4MJo3b27Wd2JjY7Ft2zYAwIgRI/Dee+9ZlYbbf89c6enpaN68uc6/1q1bo0uXLpgzZw6Ki4utShsREZVfpytfa5s3b45hw4ZZ9bumyqA9e/bg6tWrAID33nsPI0aMsGp9IirKlfT0dABA8+bNcfjwYQDA1atXsWfPHlnWI0kS1q9fL8tvEREBfI4wx82bNxEREYFNmzbpXT5t2jSMGTPG6G8YKy+seb7RR468AnTTSER0O5Yh5qlcBtxu0qRJmDRpktDv3B5r6nlHrrJA37qtIXeZR67B094JILKHixcvYujQoWjUqBGWLl2K0NBQnDhxAosWLcJvv/2GDz74QPZ1RkVF4aeffrL4+++99x68vLxkTJFlNm/ejLp16wIAioqK8Pvvv2PGjBkICgrCSy+9ZOfUERE5vylTpqBPnz46n9ny+p+RkYFXXnkF3333HQBg1KhRijTuVPbTTz+hZs2aAIBFixZBkiT07t3b6t/9448/MHv2bDzxxBNW/xYREZ8jzOPv74/7778f+/btw5AhQ3SWlZaWYv/+/ZgyZYpd0mZLt5dpREQVWIaQNbZs2YJq1arZOxnkYNi4Q25pzpw5qF+/Pj766CN4eHgAAOrXr4/IyEj07dsXX375Jfz8/GRdp7e3N2rXrm3x9wMDA+VLjBVq1aqlsx3h4eE4evQoDhw4wMYdIiIZBAQEWFVemEuSJJ2/q1evrti6b3f7NldOkzXk/C0iIj5HmK9fv3743//+h7y8PAQEBGg///XXX1FUVIQHHnjAjqmzDSXLcSJyHixDyBq1atWydxLIAXFYNnI72dnZiI+Px5gxY7SFaYV69eph0KBBOsMGLFmyBO3bt0fXrl2xbt06nfgNGzYgNjYWUVFRGDFiBE6fPq1dFhsbi4ULF6JLly4YOHAgfvvtN21X2IpupStWrECHDh0we/Zs7e/df//9aN++Pd5//32ddd3eLTQzMxOjRo1CVFQUOnfujDlz5qCkpARA+RtwS5YsQZcuXRAdHY24uDhcv35d+zspKSkYOnQo2rZti4EDB+Kvv/7SLrt48SLGjh2LiIgIxMbGYvny5SgrKzOZp97e3jp5+d1332HgwIFo27YtYmJiMGHCBNy6dQuA/u6vt3ctlSQJK1asQJcuXRATE4OxY8ciMzNTG9u8eXPs2bMHvXv3RkREBCZMmIC0tDSMHDkSERERGD58OC5fvqyN379/P/r06YOIiAgMHjwYv//+u8ntISJyRJWHB9A3TM3OnTvRr18/tGnTBsOHD0daWpre35o3bx7uv/9+ZGZmokePHgCAHj16YNu2bVWu08eOHcOwYcMQGRmJ2NhYfPnll9plkyZNwrx58/DKK68gIiIC3bp1w44dO7TLL1++jLi4OHTo0AFt2rTBI488goSEBL1pqhjC5r333sP27duxfft27ZAUZ86cwbPPPouoqCi0bdsWw4cPx9mzZ7Xf/fvvvzFixAi0a9cODz30kHYYtvT0dIwcOVLn94mILMXnCMueI7p16wZfX1/Ex8frpGvPnj3o3r07qlevjqKiIixcuBDdunVDZGQkxo4di4sXLwrtl5SUFO2zx7PPPqvz7JCQkIBhw4YhIiICkZGRGDNmDK5cuaJdvn//fjz00EOIjIzE7Nmzqzz7GNpPFcMcVf43efJkAFWHjtuyZQseffRRtGvXDqNGjUJGRgbGjx+PiIgIDBgwACkpKQDKh2MaMWIEVq5ciQ4dOuDee+/Fjh07sHfvXnTv3h0xMTFYuHChNn3FxcV466230KlTJ3Tq1AmvvfYacnJyABg+VojIPliGyF8XVdnmzZvRq1cvtGnTBp06dcKsWbMM/k5JSQmmTp2KiIgIPPDAA/jmm290ll+6dAlPPvkk2rZtiyFDhiA5OVm7zNSzyZEjRzBw4EC0a9cOL7/8MgoKCnR+21A9lb7pEJo3b659Nqs8XN6aNWvwzDPPoF27dhg8eDDOnz+PN998E1FRUejZs6f2dw8fPqwti+6991506NABH374If744w/06tULUVFReOONN6DRaACI1cu9++676NSpE8aOHWv2fiJ5sXGH3M6ff/4JSZLQtm1bvcujo6ORnJyM4uJiZGRk4PTp09i4cSMmTJiA+fPna2/S4+PjsXz5crz55pvYvn07oqOjMXLkSOTm5mp/a/fu3VizZg3+7//+DyqVqsq6jh49iq1bt2LkyJH48ccfMXfuXLzyyivYuHEjTpw4gYyMDL1pnDNnDqpVq4YdO3ZgxYoV+Pbbb7U3Ae+++y62b9+Ot99+Gxs3bsTVq1cxY8YM7Xe3bNmC0aNHY9euXahZs6Z2mSRJeOmllxAcHIzt27dj3rx52L17N1atWmUwLyVJwuHDh7F792489NBDAIALFy7g5ZdfxvDhw7Fnzx4sXboUv/zyi8Fxtiv7/PPPsXv3bixevBgbN25EcHAwRo0apb1hAIBly5bh//7v//DBBx9g3759GDZsGIYNG4YNGzYgKysLH374IQAgOTkZEydOxAsvvIBdu3ahf//+GDNmDM6fPy+UFiIiZ/Pee+9h6tSp2LZtG65fv46lS5dWifnkk0+wc+dOrFmzBvXq1cPmzZsBlD8MVR4O7uzZs3jqqafQoUMHbNu2DePHj8f8+fOxf/9+bcz69evRunVrfPXVV+jZsydmzJiBvLw8AMBrr72GsrIybNiwATt27EBoaChmzpxpdBtGjRqF3r17o3fv3tiyZQs0Gg3Gjh2LsLAw7Ny5Exs2bEBZWZm2cquwsBBjxoxBdHQ0du3ahYkTJ+L999/Hjh07ULduXe3D6E8//YSoqChLs5aIiM8RFj5HeHt748EHH8S+ffu0v1VSUoLvvvsO/fr1AwDMmDED+/fvx/z587FhwwaUlpbixRdf1FY0GfPll19i9OjR2Lp1K0pLSzFx4kQAQF5eHp5//nnce++9+Oqrr7BmzRpcuHABq1evBlBeOffKK69g2LBh2u/e/gKCsf1UMcxRxb+FCxfC29vb4BCgS5cuxauvvoovvvgCp06dwiOPPIJ77rkHW7ZsgZ+fH5YsWaKNPXbsGNLS0rBlyxb07dsXM2fOxGeffYaVK1di0qRJ+Oijj3Dq1CkA5ZW/J0+exIcffojPPvsMN2/exMsvv6yz7tuPFSKyH5Yh8tVF6fP777/jrbfewoQJE7B3717MmjULW7Zs0Q49XdmxY8cAlDeqDxs2DK+99ppOXdH27dvRq1cv7NixA/Xr18dLL72EsrIyk88m165dw/PPP4977rkHO3bsQJMmTbB3717t7xqrp6pbt65O2fLJJ5/Ay8sLzzzzjN5tWLFiBYYMGYJt27YhLy8PgwcPRkhICLZs2YKmTZvirbfe0sZeuXIFBw4cwLp16zB27FgsWbIEb7/9Nv7v//4PS5YswTfffKPNK5F6uYMHD+LLL7/Ea6+9ZtZ+IhuQiNzMzp07pWbNmkklJSV6l//4449Ss2bNpFWrVklt27aVrl27pl02adIk6ZVXXpEkSZKGDRsmffbZZzrffeSRR7Sfde/eXVq4cKF22W+//SY1a9ZMkiRJSktLk5o1ayYdOnRIu3z8+PHS5MmTtX9fu3ZNatu2rbR161ZJkiTpySeflJYtWyZJkiQ9/PDD0qRJk6Ti4mJJkiTpzz//lNLS0iSNRiN17NhR+x1JkqSUlBTt97p37y4tXrxYu2z//v1S27ZtJUmSpF9++UW6++67pbKyMu3y7777TurYsaNOmiMiIqTIyEgpMjJSatWqldSlSxdp2bJlUmlpqSRJknTu3Dnpyy+/1MmX//3vf9ptW7ZsmfTkk0/qLO/evbs2zffdd5/03XffaZeVlpZKd999t/azZs2aSRs2bNAuHzx4sPT6669r/16wYIE0atQoSZIk6bXXXpPmzZuns66XXnqpymdERI6ie/fuUps2bbTX2Yp/t27d0ikHJOm/63JaWpokSeXXx88//1y7fO3atVLPnj0lSfqvDPr666+l9u3bS8ePHzf4O7dfp99++23p8ccf10njwoULpSFDhkiSJEkTJ06UBg0apF2Wl5cnNWvWTEpISJA0Go306aefShcvXtQu/+GHH6QWLVoYTP9vv/2m/d2JEydKkiRJt27dkj788EPp1q1b2t/58ssvpR49ekiSJEmbNm2SHnnkEZ00fvbZZ9rPbi9/iYiswecIy54jJEmSfv75Z6ldu3baa/n3338vdezYUSouLpZycnKkFi1aSD/++KM2/vr161JERIT0ww8/GC0vunfvLv3f//2f9nsVsWfOnJGuXLkirVmzRtJoNNrlixYtkkaOHClJkiT93//9n/b/kiRJxcXF2mcbkf1U4eLFi1KnTp10yuDKabw9715++WVp+PDh2r/Xr1+vLa+3bt0qtWrVSptPZ86ckZo1ayb98ssv2vjOnTtLu3fvlvLz86XWrVtLycnJ2mW5ublSixYtpOTkZL3HChHZD8sQ+eqibq+TqnhmOHHihLR7926dfBkyZIi0fPlySZJ0ny+WLVsmdenSRbsdFdtZkW9PPvmkNH78eO2yvLw8KTIyUjp06JDJZ5PPP/9ceuCBB3TKnkcffVS7btF6qry8PKlnz57S/PnztZ/dXnf25JNPShMmTNAuW7BggXT//fdr1/v9999LrVu3liTpv2MgNTVVkiRJKigokJo1ayZt3rxZ+/3BgwdLq1atkiRJrF7uiy++kMgxcM4dcjsVE1tmZ2fjjjvuqLK8opt+zZo1Ub9+fQQFBWmXtWrVSvuG89mzZ7Fw4UKdt6yKiorwzz//aP8OCwszmpbbl589exZDhw7V/h0UFIT69evr/d7o0aMxZcoU7N+/H/fddx/69OmDVq1a4dq1a8jJyUHr1q21sU2aNMH48eO1f9/+mwEBASgqKtKuPycnB9HR0drlGo0GhYWFOl1pV69ejdDQUGRmZmL27Nlo0aIFxo4dq+1WfNddd8Hb2xsrV65ESkoKUlJScObMGQwYMMBoXgDArVu3cOnSJfzvf/+DWv1fx8LCwkKdfL19G3x9fXXy0dfXF8XFxdpt2rNnDzZu3KhdXlJSgi5duphMCxGRvcTFxaFnz546n4mOvd2gQQPt//39/XXergLKh1Hz9vbWW/7pc/bsWbRr107ns6ioKGzYsEH791133aWzTqB8WAaVSoVhw4bhm2++wdGjR3Hu3DmcPHlS6C3s21WrVg3Dhg3Djh07cPLkSaSmpuLUqVMICQkBAKSmpiI5OVmnV05ZWVmV4S6IiKzF5wjLniOCgoLQqVMnBAQE4IcffkCvXr2wd+9ePPTQQ/Dy8sI///wDjUaDiIgI7fcDAwPRsGFDnD17Fg0bNjSaF7eXU+Hh4QgMDERqaioefPBBDBw4EJ9++in++usvnDlzBqdPn0b79u216W7ZsqX2u15eXjp/i+yn4uJixMXF4Z577jHYa6dy3ul7frm9vA4ODtZOmO3j46Pdrtvji4uLkZaWhpKSEp19D5Tn/T///KPdl6aOJSJSBssQeeqibrdo0SLt/9u0aQNfX18sW7ZMe70/f/68wfqfli1bwsvLS/t369atdYZWu71s8ff3R8OGDZGamor77rvP6LPJmTNn0KJFC50eU23bttUOzSZaTzV58mQEBwdjwoQJetMPVC0b6tWrp11v5bIF+G8f+Pr6AoDeujTRejmWLY6DjTvkdtq2bQsPDw+cPHlSb4F68uRJNG/eHN7e3joXMqC8gKm4+JeVlWHKlCno3LmzTkxFxRbw3824IZWXS5Umfb69oLld//790blzZxw4cADff/894uLiMGbMGDz77LNG1wfAYGVXaWkpGjVqVGV8VaC84K2YM6devXoIDw9HgwYN8MEHH2DAgAGYP38+pk2bBqC8i+mwYcMQGxuLmJgYPP3001i7dq32t/R1CS4tLQUA7Vio7777bpWHuIobIX3bUHk/VSgrK8OYMWMwcOBAnc8rCjIiIkcUHBys00hjiL7xow2VGxUWLlyIjz76CPPnz9d5GDJEXzmm0Wh01q1vnZIkQaPRYNSoUbhx4wb69OmD2NhYlJSU4KWXXjK53tvdunULgwcPRlBQEGJjY9GvXz+kpqbi448/BlBehnTu3BnTp08363eJiMzF5wjLniMqvturVy/s378fPXr0wIEDB7BixQq921KhYvgbc9NVkdeXL1/Go48+itatW+Oee+7BkCFD8P333yMpKUkbayzfRPbTvHnzcOPGDcyZM8esNBp6fgEAT8+q1TT6nqEqyuIvvvhC2xhUITg4WDv3jqljiYiUwTJEnrqo21WvXl37/x9//BHjxo3DwIED0bVrV4wbNw6zZs0ymB5jeawvvRXLTT2bAPrzs6JxR6Se6qOPPsKRI0ewY8cOvWVChcrLjJUtovGi9XIsWxwH59wht1OrVi088MADeP/996tUjF28eBFbtmzBkCFDAABpaWk6E58dP34cjRo1AgA0bNgQly5dQoMGDbT/Vq1ahcTERIvS1bRpU5w4cUL7982bNw3ODfPOO+/g6tWrGDZsGD744AO88sor2LdvH2rUqIGgoCCdid7++usv3HfffSgsLDS6/oYNGyIzMxO1atXSbk96ejqWLVum92ECAO68806MHz8en3/+ufYhaefOnejQoQMWL16M4cOHo127djh//ry2cKsoDCvcunUL165dAwDUqFEDwcHByMrK0qahbt26WLhwIc6dOyeQi1W3KT09XWcfbdy4ET/88IPZv0VEZG/e3t4618+0tDSzf+Ohhx7CtGnT8PXXX+OPP/4AoL/CqELDhg11KsGA8vGpTb1FDZS/tfbHH3/g008/xdixY3H//fdr30is/MBT2e1p+v3333HlyhV89tlnGD16NO655x5kZmZqf6Nhw4Y4d+6c9sWDBg0aIDExUTvxrLHtIyIyB58j9BN9jujXrx8OHTqEX375BdWqVUOHDh0AlL9J7OnpqbP9169fx/nz54XKm7///lv7/3/++Qc3btxAw4YNsX//ftSsWRMffPABnnrqKcTExCAtLU1bflTON41Go7P9pvbTzp07sW3bNrz77rs6FYxKqV+/Pjw8PJCTk6NNn7+/P+bNm4erV68qnh4iMo5liH6W1EXps3nzZjz66KOYPXs2HnvsMTRu3BgXLlww+NyRkpKi8/fteQzoli03btzAP//8g0aNGpl8NmnatClOnTqls4//+usvne01Vk91+PBhLF26FIsWLarSU0kJctfLke2xcYfc0tSpU5Gbm4sxY8bgyJEjyMzMxP79+zFy5Eh07NgRw4cPB1DetXXixIlISUnBhg0b8O233+Kpp54CADzzzDNYu3YtduzYgQsXLmDhwoXYs2cPGjdubFGannzySezZswebNm3C2bNnMX36dIOFYGpqKmbPno3k5GSkpKTg0KFDaNWqFQBgxIgRePfdd/Hbb78hJSUFc+fORWRkpMneKl26dEFYWBhef/11nD59GkeOHMGbb74JPz8/o0PbjBw5Eo0bN8bs2bOh0WgQGBiI06dP4/jx4zh37hz+7//+DydOnNAOlda2bVskJydjz549OHfuHKZPn67ztsDTTz+NpUuXIj4+Hv/88w+mTZuGo0eP6hSyop5++ml88803+Oyzz3DhwgV8+umn+PTTT3WGECIichZt2rTBnj17cPz4cRw/fhzLli2z6HciIiIwYMAAzJ49G6Wlpdoh35KTk3UajwBg+PDh+Ouvv7BkyRKcO3cO27dvxxdffGF06JkKNWrUgFqtxtdff42MjAzs3bsX7733HgBoywRD/Pz8kJGRgcuXLyMwMBD5+fk4cOAA0tPTsXnzZqxfv177G/3790dhYSGmT5+Os2fP4tChQ5g7dy6Cg4O1vwWUvw1ZMfwDEZGl+BxRlehzRGRkJAIDA/HOO++gT58+2kq76tWr47HHHsOcOXNw+PBhJCcn4/XXX8cdd9yBe++91+T2f/LJJ9i3bx+Sk5MxefJkdO/eHQ0aNEBgYCAyMzPx66+/Ii0tDatXr8a+ffu05ceQIUNw8uRJrFy5EqmpqZg/fz4yMzO1v2tsP50+fRozZszAxIkTERISgqysLGRlZWlfWlOCv78/HnvsMcycOROHDx/GmTNn8MYbb+D8+fNV3m4nIsfAMqQqS+uiKgsMDMSxY8dw+vRppKSkYNKkScjKyjL43JGZmYk5c+bg7NmzWLFiBU6dOoVhw4Zpl+/evRubNm3CmTNnMGXKFDRo0AB33323yWeTvn37oqCgAHPnzkVqaio++ugjJCQkaH/XWD3V5cuXMWHCBDzzzDNo2bKltmzJysoSzgc5yFkvR7bHYdnILYWGhmLTpk14//338dprr+HatWuoX78+hg4diqeeekrb2NCyZUuEhoZiyJAhCAoKwttvv402bdoAAPr06YPs7GwsW7YM2dnZaNKkCVauXGlxw0FMTAzmzZuHpUuX4tq1a3j00Ud1xny+3cyZMzFr1iyMGDECpaWluP/++zF16lQAwHPPPYe8vDy88sor2mVvvvmmyfV7eHhg5cqVmDNnDoYMGYJq1aqhV69emDhxotHveXp6Ytq0aXj66aexdetWjBgxAqdOncLTTz8NHx8fdOjQAePGjcPXX38NAOjcuTOefvppbaPOM888o32TGwCeffZZ3Lp1C9OnT8fNmzfRpk0brFmzRqf7p6jIyEgsWLAA7733HhYsWIA777wTixcv1r4lSETkTJ555hn8/fffePLJJxEaGoqpU6fi+eeft+i3Xn31VTz00ENYt24dnnnmGfTv3x+vvPIKXnvtNZ24evXq4YMPPsCCBQvw8ccfo169epg0aRIeffRRk+u44447MHPmTKxYsQJLlixBw4YNMW3aNEycOBGnTp1C7dq1DX53wIABGDduHPr374/ffvtNO6xCUVERmjdvjunTp2Pq1Km4fPkyQkND8eGHH+Ltt9/GwIEDERgYiCeeeEKbN82bN8e9996LoUOHYsmSJVXmMyIiMgefI6oy5zmib9++WLVqFd5++22dzydOnIj58+cjLi4OxcXFuOeee/Dpp5/C29vb5PqfeeYZLF26FOnp6bjvvvswe/ZsAEDv3r3xxx9/IC4uDiqVCm3btsXEiRPx3nvvobi4GA0aNMDKlSsxb948rFy5Eg888AC6deum/V1j++m9995DQUEBZs2apTPsT1hYGOLj402mWS6TJk3S5ltJSQk6dOiA1atXc945IgfFMqQqS+uiKnvppZcwefJkPP744/D390e3bt0wbNgwnV4zt+vWrRtycnLwyCOPICwsDCtXrtTpKTNixAhs2bIFc+bMQVRUFJYvXw6VSoWoqCiTzyYfffQRZs6ciQEDBqBDhw4YMGCAtmePsXqqbdu2ITs7G6tXr8bq1at10nv69Gmz8sMactbLke2pJFPjYhAREREREREREREREZHD4LBsREREREREREREREREToSNO0RERERERERERERERE6EjTtEREREREREREREREROhI07REREREREREREREREToSNO0RERERERERERERERE6EjTtEREREREREREREREROhI07REREREREREREREREToSNO0RERERERERERERERE6EjTtEREREREREREREREROhI07REREREREREREREREToSNO0RERERERERERERERE6EjTtEREREREREREREREROhI07RERERERERERERERETsTT3glwZVev5kGSzPuOSgUEBwdY9F13xTwzD/PLfMwz81ibXxXfp/+wPFEG88x8zDPzML/MZ02esTypytqymceuY+F+cUzcL46J5Yn8+IyiDOaZeZhf5mOemcfR6rzYuGNDkgSLTwprvuuumGfmYX6Zj3lmHuaXfFieKIt5Zj7mmXmYX+ZjnsnD2nzkfnBM3C+OifvFMXG/yIfPKMpinpmH+WU+5pl5HCW/OCwbERERERERERERERGRE2HjDhERERERERERERERkRNh4w4REREREREREREREZETYeMOERERERERERERERGRE/G0dwKISDllGgmJGbkoSr8BH40GkWE14aFW2TtZRCQznutEREREROV4b0zkHniukzti4w6Rm4hPycbi+DO4crNY+1kdf2+8GtsEsU1D7JgyIpITz3UiIiIionK8NyZyDzzXyV1xWDYiNxCfko2Ju07pFHIAcOVmMSbuOoX4lGw7pYyI5MRznYiIiIioHO+NidwDz3VyZ2zcIXJxZRoJi+PPGI1ZcvAsyjSSQikiIlvguU5EREREVI73xkTugec6uTs27hC5uMSM3CpvL1R2Oa8IiRm5CqWIiGyB5zoRERERUTneGxO5B57r5O7YuEPk4rJNFHLmxhGRY+K5TkRERERUjvfGRO6B5zq5OzbuELm4WtW8ZI0jIsfEc52IiIiIqBzvjYncA891cnds3CFycaKjinL0USLnxnOdiIiIiKgc742J3APPdXJ3bNwhcnHX80tkjSMix8RznYiIiIioHO+NidwDz3Vyd2zcIXJxIf7essYRkWPiuU5EREREVI73xkTugec6uTs27hC5uMiwmqhjohALDfBBZFhNhVJERLbAc52IiIiIqBzvjYncA891cnds3CFycR5qFV6NbWI0ZkL3xvBQqxRKERHZAs91IiIiIqJyvDcmcg8818ndsXGHyA3ENg3B/P6tqrzNEBrgg/n9WyG2aYidUkZEcuK5TkRERERUjvfGRO6B5zq5M097J4CIlBHbNATdGgcjMSMXRWo1fDQaRIbV5NsLRC6G5zoRERERUTneGxO5B57r5K7YuEPkRjzUKsTcGYiQkABkZ+dBkuydIiKyBZ7rRERERETleG9M5B54rpM74rBsRERERERERERERERETsSujTvFxcWYNWsWOnTogHvuuQdLliyB9G+z6qlTp/DYY48hIiICjz76KE6ePKnz3a+++goPPPAAIiIiMG7cOFy7dk27TJIkLFq0CHfffTc6duyIBQsWQKPRaJdfv34d48ePR1RUFGJjY7Fz506d3za1biIicjwsU4iISA4sT4iISA4sT4iIyNbs2rjz1ltv4ZdffsGaNWuwePFibNq0CRs3bkR+fj6ee+45xMTEYNu2bYiKisLzzz+P/Px8AMDx48cxdepUvPTSS9i4cSNu3LiByZMna3/3k08+wVdffYXly5dj2bJl2L17Nz755BPt8smTJyMvLw8bN27ECy+8gGnTpuH48eMAYHLdRETkmFimEBGRHFieEBGRHFieEBGRrdltzp2cnBxs3boVn3zyCdq1awcAGDVqFJKSkuDp6QkfHx+88cYbUKlUmDp1Kn744Qfs3bsXgwYNwueff47evXtj4MCBAIAFCxage/fuSEtLQ/369fHZZ58hLi4OMTExAIDXXnsN7777Lp599llcuHABBw8exHfffYfw8HA0a9YMiYmJ+OKLL9CuXTt88803RtdNRESOh2UKERHJgeUJERHJgeUJEREpwW49dxISEuDv74+OHTtqP3vuuecwb948JCUlITo6GiqVCgCgUqnQvn17JCYmAgCSkpK0hRgA1K1bF/Xq1UNSUhIuX76MixcvokOHDtrl0dHRyMjIwJUrV5CUlIS6desiPDxcZ/mxY8e0v21s3URE5HhYphARkRxYnhARkRxYnhARkRLs1nMnLS0NYWFh2LFjB1atWoWSkhIMGjQIL7zwArKystCkSROd+ODgYKSkpAAArly5gjp16lRZfunSJWRlZQGAzvKQkBAA0C7X993Lly8DgMl1m+PfstKi71jyXXfFPDMP88t8zDPzWJtflnzP1csUlifKYJ6Zj3lmHuaX+azJM5YnVVlbNvPYdSzcL46J+8UxsTxhnZezYp6Zh/llPuaZeexR52WM3Rp38vPzcf78eWzYsAHz5s1DVlYWpk+fDj8/PxQUFMDb21sn3tvbG8XFxQCAwsJCg8sLCwu1f9++DCifzM7Ub5tabo7g4ACzvyPHd90V88w8zC/zMc/Mo2R+uXqZwvJEWcwz8zHPzMP8Mp9SecbyxLbfJ9vgfnFM3C+OieUJ67ycFfPMPMwv8zHPzOMo+WW3xh1PT0/cvHkTixcvRlhYGAAgMzMTX375JRo0aFClYCkuLoavry8AwMfHR+9yPz8/nULNx8dH+38A8PPzM/hdU79dsdwcV6/mQZLM+45KVX5wWPJdd8U8Mw/zy3zMM/NYm18V3zeHq5cpLE+UwTwzH/PMPMwv81mTZyxPqrK2bOax61i4XxwT94tjYnnCOi9nxTwzD/PLfMwz89ijzssYuzXu1K5dGz4+PtpCDgAaNmyIixcvomPHjsjOztaJz87O1nYtDQ0N1bu8du3aCA0NBVDe1bRijNGKbqsVyw1919hvV+7WKkKSYPFJYc133RXzzDzML/Mxz8yjZH65epnC8kRZzDPzMc/Mw/wyn1J5xvLEtt8n2+B+cUzcL46J5QnrvJwV88w8zC/zMc/M4yj5pbbXiiMiIlBUVIRz585pP0tNTUVYWBgiIiJw7NgxSP/mkCRJOHr0KCIiIrTfTUhI0H7v4sWLuHjxIiIiIhAaGop69erpLE9ISEC9evVQp04dREZGIiMjA5cuXdJZHhkZqf1tY+smIiLHwzKFiIjkwPKEiIjkwPKEiIiUYLfGnUaNGuH+++/H5MmTkZycjB9//BGrV6/GsGHD0KtXL9y4cQNz587FmTNnMHfuXBQUFKB3794AgGHDhmHnzp3YvHkzkpOT8cYbb+D+++9H/fr1tcsXLVqEw4cP4/Dhw1i8eDFGjhwJAKhfvz66dOmC119/HcnJydi8eTO++uorPPHEEwBgct1EROR4WKYQEZEcWJ4QEZEcWJ4QEZESVJJkvw5EeXl5mDNnDvbv3w8/Pz8MHz4c48aNg0qlwvHjxzFjxgycPXsWzZs3x6xZs9CqVSvtd7dt24Zly5YhNzcX9957L+bMmYOgoCAAQFlZGRYsWIBt27bBw8MDgwcPxquvvgqVSgUAuHr1KqZOnYpffvkFtWvXxv/+9z/069dP+9um1i0qO9uy8UdDQgIs+q67Yp6Zh/llPuaZeazNr4rvm8uVyxSWJ8pgnpmPeWYe5pf5rMkzlidVWVs289h1LNwvjon7xTGxPGGdl7NinpmH+WU+5pl57FXnZfD37Nm44+pY0CmDeWYe5pf5mGfmcbSCzhWwPFEG88x8zDPzML/MZ4/KOFfGxh3Xwv3imLhfHBPLE/nxGUUZzDPzML/Mxzwzj6PVedltWDYiIiIiIiIiIiIiIiIyHxt3iIiIiIiIiIiIiIiInAgbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt3iIiIiIiIiIiIiIiInAgbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt3iIiIiIiIiIiIiIiInAgbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt3iIiIiIiIiIiIiIiInAgbd4iIiIiIiIiIiIiIiJwIG3eIiIiIiIiIiIiIiIicCBt3iIiIiIiIiIiIiIiInIinvRNARMop00hIzMhFUfoN+Gg0iAyrCQ+1yt7JIiKZ8VwnIiIiUh7vwYhITrymEJEpbNwhchPxKdlYHH8GV24Waz+r4++NV2ObILZpiB1TRkRy4rlOREREpDzegxGRnHhNISIRHJaNyA3Ep2Rj4q5TOjcFAHDlZjEm7jqF+JRsO6WMiOTEc52IiIhIebwHIyI58ZpCRKLYuEPk4so0EhbHnzEas+TgWZRpJIVSRES2wHOdiIiISHm8ByMiOfGaQkTmYOMOmVSmkZCQloNv/7qChLQcFiBOJjEjt8rbHpVdzitCYkauQikiIlvguU5ERESkPN6DOb4yjYQjF3KwMzEDRy6wToMcG68pluO5Tu6Ic+6QUY4+xicnlzMt28RNgblxROSYeK4TERERKY/3YI7N0es0iCrjNcUyPNfJXbFxhwyqGOOzsooxPuf3b2XXCyQv3GJC/L1ljSMix8RznYiIiEh5vAdzXI5ep0GkD68p5uO5Tu6Mw7KRXo4+xicnlxMXGVYTdUwU+qEBPogMq6lQiojIFtrWrQFT/RZV/8YRERERkTz4vOWYyjQS3t73t9GYt/f9zWGbyOHwmmIenuvk7ti4Q3o58hifjt7w5Gg81Cq8GtvEaMyE7o05nB2Rk0vMyIWpq570bxwRERERyYPPW44pIS0HuYWlRmNyC0uRkJajTIKIBPGaYh6e6+Tu2LhDejnyGJ+O3PDkqGKbhmB+/1ZV3v4IDfBh91QiF3E0PUfWOCIiIiISw+ctx8N7Y3JmvKaI47lO7o5z7pBejjzGpyM3PDmy2KYh6NY4GIkZuShSq+Gj0SAyrCbf9iByEZJgZ0XROCIiIiISx+ctx8J7Y3J2vKaI4blO7o49d0gvRx7j05EbnoiI7CWmfqCscUREREREzor3xuQKPNQqxNwZiAGRYYi5M5ANO3rwXCd3Z9fGnf3796N58+Y6/+Li4gAAp06dwmOPPYaIiAg8+uijOHnypM53v/rqKzzwwAOIiIjAuHHjcO3aNe0ySZKwaNEi3H333ejYsSMWLFgAjUajXX79+nWMHz8eUVFRiI2Nxc6dO3V+29S63YEjj/HpyA1Pjiw+JRv9PzyMsZuO4+UNiRi76Tj6f3gY8SnZ9k4akSzcvUxpXz8QNXyNd8it6euJ9rypJSIyyt3LEyKyDJ+3HIsj3BuzPCGyPUc414nsya6NO2fOnEH37t3x008/af+99dZbyM/Px3PPPYeYmBhs27YNUVFReP7555Gfnw8AOH78OKZOnYqXXnoJGzduxI0bNzB58mTt737yySf46quvsHz5cixbtgy7d+/GJ598ol0+efJk5OXlYePGjXjhhRcwbdo0HD9+HABMrtudOOoYn47c8OSo4lOyMXHXqSpzFV25WYyJu07xgYNcgruXKR5qFQa0ucNoTP82d/DaSERkgruXJ0RkPj5vOR4PtQpTezYzGjOlZzOb3huzPCFrlWkkHLmQg52JGThyIQdlGo4tVhmfg8nd2bVx5+zZs2jWrBlq166t/VejRg1888038PHxwRtvvIHGjRtj6tSpqF69Ovbu3QsA+Pzzz9G7d28MHDgQLVq0wIIFC3Do0CGkpaUBAD777DPExcUhJiYGd999N1577TWsX78eAHDhwgUcPHgQb731Fpo1a4bHHnsM/fv3xxdffAEAJtftbmKbhmDXmE5YNaQd3urTAquGtMPO0R3tPnmbozY8OaIyjYTF8WeMxiw5eJY3CeT03L1MKdNI+Db5itGYfaezeK4TEZng7uUJEZmHz1uOK7ZpCEbEhKNyla4KwIiYcJvXG7A8IWuwN6AYPgeTu7N7485dd91V5fOkpCRER0dDpSovglUqFdq3b4/ExETt8piYGG183bp1Ua9ePSQlJeHy5cu4ePEiOnTooF0eHR2NjIwMXLlyBUlJSahbty7Cw8N1lh87dkxo3e7IQ61CdP1APNSyDqLrO84Yn7c3PL07NNJhGp4cTWJGbpU3yCq7nFeExIxchVJEZBvuXqbwXCcikoe7lydEZB7egzmu+JRsrDuSjspVuhKAdUfSbV5JzvKELMXegOJ4DSZ3Z3xQQhuSJAnnzp3DTz/9hA8++ABlZWXo1asX4uLikJWVhSZNdIfdCg4ORkpKCgDgypUrqFOnTpXlly5dQlZWFgDoLA8JKa/sr1iu77uXL18GAJPrNofKgjaQiu9Y8l135OmhQocGgQgODsDVq3mQ2BBfxZWbRcJxPO7043lpHmvzy5LvuXqZIpInPNetx3PdfMwz8zC/zGdNnrE8qcraspnHrmPhfnEM2beMVyreHsd9pRzRHlX3Nwk2+QIryxP9WOdlG3Ieu+6A12Dr8bw0jz3qvIyxW+NOZmYmCgoK4O3tjaVLlyI9PR1vvfUWCgsLtZ/fztvbG8XF5SdsYWGhweWFhYXav29fBgDFxcUmf9vUcnMEBweY/R05vuuumGf6laiyBOPUCAlhHhrDY8w8SuaXq5cpInnJc10+PNfNxzwzD/PLfErlGcsT236fbIP7xb4a1xM7DxvXC+Q9mIJ+PXtV6G3+1LwSdG4cLPv6Xb08AVjnZSv2PnadDa/B8uF5aR5HyS+7Ne6EhYXh8OHDqFmzJlQqFVq2bAmNRoPXX38dHTt2rFKwFBcXw9fXFwDg4+Ojd7mfn59Ooebj46P9PwD4+fkZ/K6p365Ybg5LepKoVGAvFDMxz4zzkjTCcdnZeTZOjXPiMWYea/Or4vvmcPUyRSQvea5bj+e6+Zhn5mF+mc+aPGN5UpW1ZTOPXcfC/eIYGgV4oY6/t9HK2NAAHzQK8OI9mILOZuYIxzWt6W00huWJfqzzsg05j113wGuw9XhemscedV7G2K1xBwACAwN1/m7cuDGKiopQu3ZtZGfrjh+ZnZ2t7VoaGhqqd3nt2rURGhoKoLyracUYoxXdViuWG/qusd+u3K1VhCTB4pPCmu+6K+aZfnX8fYTjmH/G8Rgzj9L55cplikhe8lyXD8918zHPzMP8Mp+Seebu5Yktv0+2wf1iX2qVCq/GNsHEXacMxkzo3hhqlYr7SUEh1cUqvUOqe9tsv7hyeQKwzstWHOHYdSa8BsuH56V5HCW/1PZa8Y8//ohOnTqhoKBA+9lff/2FwMBA7WRv0r85JEkSjh49ioiICABAREQEEhIStN+7ePEiLl68iIiICISGhqJevXo6yxMSElCvXj3UqVMHkZGRyMjIwKVLl3SWR0ZGan/b2LqJnE1kWE3U8Td+cxAa4IPIsJoKpYhIfixTeK4TEcmB5QkRWSK2aQjm929V5V4sNMAH8/u3QmzTEDulzH3Z+96Y5QlZyt7HrjPiNZjcmd0ad6KiouDj44Np06YhNTUVhw4dwoIFCzB69Gj06tULN27cwNy5c3HmzBnMnTsXBQUF6N27NwBg2LBh2LlzJzZv3ozk5GS88cYbuP/++1G/fn3t8kWLFuHw4cM4fPgwFi9ejJEjRwIA6tevjy5duuD1119HcnIyNm/ejK+++gpPPPEEAJhcN5Gz8VCXv8VgzITujTkRHzk1lik814mI5MDyhIgsFds0BLvGdMKqIe3w7tBIrBrSDjtHd2Slop3Y+96Y5QlZyt7HrrPiNZjclUqS7NeBKCUlBW+//TYSExNRvXp1DB06FOPGjYNKpcLx48cxY8YMnD17Fs2bN8esWbPQqlUr7Xe3bduGZcuWITc3F/feey/mzJmDoKAgAEBZWRkWLFiAbdu2wcPDA4MHD8arr74Klar8wnf16lVMnToVv/zyC2rXro3//e9/6Nevn/a3Ta1bVHa2ZeOPhoQEWPRdd8U8ExOfko3F8Wd0xiENDfDBhO6NWdiZwGPMPNbmV8X3zeXKZYo5eclz3XI8183HPDMP88t81uQZy5OqrC2beew6Fu4Xx8T94ljkuDdmeaIf67xsi891luExZj7mmXnsVedl8Pfs2bjj6ljQ2V6ZRkJiRi6K1Gr4aDSIDKvJtxeMKC7VYEtSJq4WlSHYxwODI+rB29NuHficBs9L8zhaQecKzM3LguIyLPshFZfzSxBazQtx9zWCn7eH7RLoInium495Zh7ml/ns0bjjyti441q4XxwT94vjsfbemOWJfqzzsj3W4ZiHdYSW4XlpHker8/KU7ZeIFKbvLYY6/t54NbYJ32LQQ19+rT+SzvwicjHLDqVifUI6NLfdZGw7fhFPRIcjrlsj+yWMiIiIiEhhvDcmZ8U6HPOwjpDcFZt7ySnFp/w/e3ce3lSx/gH8m3RJW7pBN6BlLfvWlhYQBZGqiIoFEVFQXHABRVBBZBUQRX6A4IaKiFwV8SqIsioqlovrRSi2hQtoCwhtWdog3eie5PdHbaRtmsxpT3JOku/neXiU5E0yTE7Oe2bmzIwes7YfrXXSBoDc4grM2n4UyRl6hUqmTqwvIvfw+r6T2HCwduMVAIwmYMPBbLy+76QyBSMiIiIicjBeG5OzYh+ONKwvcmcc3CGnYzCa8NI3f1iNeembP2CoewXnpgxGE1YmZ1qNWbX3hOL1ZTCakJKVj6+P5SIlK1/x8hA5m4oqIz46mG015qOD2aioMjqoREREREREyuC1MTkr9nlJ4yx9XkT2wsEdcjopWfkoKKuyGlNQVoWUrHzHFEjlUnMK6t29UNeFonKk5hQ4qET1JWfokfTufkzelI75Xx7H5E3pSHp3P++uIJJg0285sHW5avo7joiIiIjIlfHamJwV+7ykcYY+LyJ74uAOOZ1D2fmyxrk6vY0kJzVObpw+SySPtLNiF6uicUREREREzorXxuSs2Ocljdr7vIjsjYM75HRMgjMpReNcXai/t6xxcuL0WSL5+Hh6yBpHREREROSseG1MzsoouFKgaJyrU3OfF5EjcHCHnE5Cm2BZ41xdbGQQwm0ksYgAHWIjgxxUon9w+iyRfDqHN5M1joiIiIjIWfHamJxVoK+nrHGuTs19XkSOwMEdcjp92wQj0Md6Egvy8URfDu4AADy0GtzULdxqzLCuYfDQahxUon9w+iyRfMKa6WSNIyIiIiJyVrw2JmcV4ic2w0Q0ztV5aDWYkdjJasz0odGK9HkROQIHd8jpeGg1mDesi9WYucO68MT9N4PRhG1HzluN2X7kvCJLn3H6LJF8QpsJ/p4E44iIiIiInBWvjclZ8diVLrFzKJYl9ag3gyciQIdlST2Q2DlUoZIR2R/n8JFTqjlxv/xdBvIuV5ofD/f3xozETjxxX+FQVj4Ky6qsxhSUVeFQVj76tWvuoFJVq5k+a21pNk6fJRJjENxoTDSOiIiIiMhZ8dqYnBWP3cZJ7ByKIdEhSM0pQLlWC53RiNjIIN74TS6PgzvktHjiFnMwK184ztGDOzXTZ2dtP9pgDKfPEon5LVtsb6rfsgtwVfsWdi4NEREREZFyeG1MzorHbuN5aDVIaBuM0NAA6PVF4PgXuQMuy0ZOrebEPTI2EgltgzkIYIFGsEpE4+TG6bNE8lD7b52IiIiIyFF4bUzOiscuEUnBmTtELq5vVDDeQ5ZQnFKunIWlL65AqL83Z2ERSeQMv3UiIiIiIkfgtTE5Kx67RCQFB3eIXFx8m2AE+XiiwMq+O0E+nohvE+y4QlngodUoXgYiZ+Ysv3UiIiIiInvjtTE5Kx67RCQFl2UjcnEeWg3mDutiNWbusC6cJUPk5PhbJyIiIiKqxmtjclY8dolICg7uELmBBve18ee+NkSuhL91IiIiIqJqvDYmZ8Vjl4hEcVk2Ijdx5b425VotdEYj97UhckH8rRMRERERVeO1MTkrHrtEJIKDO0RuxEOrQULbYISGBkCvL4LJpHSJiMge+FsnIiIiIqrGa2NyVjx2icgWLstGRERERERERERERETkRDi4Q0RERERERERERERE5EQatSzbiRMnEB4ejoCAAPzwww9ITk5Gjx49cOedd8pdPiKnZDCakJpTAH1xBUL9vbkuKlEDTp/+EyEhofD398f+/b/gxx+/R9euXfHggxOULppTqzkHlWcXcm1mInIbdXPKTz99j759Y9hGISJyc1KvjZlPSC3YriMiWyQP7nz66adYvHgx/vWvf8Hf3x+PPfYYrrrqKnz77bc4e/YsnnzySXuUk8hpJGfosTI5E7nFFebHwv29MSOxExI7hypYMiJ12bbtc6xatQyvvvoWmjVrhtmzp6Nv3374/vtkFBb+xXzSSDwHEZE7spRT4uP74Ycf/sM2ChGRG5N6bcx8QmrBdh0RiZC8LNu6deuwbNky9O/fH1u2bEH37t2xbt06vPLKK9i8ebM9ykjkNJIz9Ji1/Wit5AsAucUVmLX9KJIz9AqVrJrBaMLBM/nYlpqDg2fyYTByNz5Szscff4j5859HXFw8du3ajk6dumDlytexePFS5pNGUvs5iIjIXhrKKWyjEBG5r8ZcGzOfkBqwXdc47PMidyR55s6FCxcQHx8PANi7dy/uuusuAEDLli1x+fJleUtH5EQMRhNWJmdajVm19wSGRIcoMo2Wd32Q2uTl5aFPn1gAwE8//YCRI0cDAMLCwplPGkHt5yAiIntqKKewjUJE5J4ae23MfEJKY7uucdjnRe5K8sydjh07YseOHfjss89w9uxZ3HDDDaisrMT69evRrVs3e5SRyCmk5hTUu6uirgtF5UjNKXBQif7Buz5Ijdq1a4dvvtmNnTu34cKF8xg8+DpUVVXhk082Mp80gprPQURE9tZQTmEbhYjIPTX22pj5hJTGdp107PMidyZ55s6sWbPw1FNPoaCgAOPHj0d0dDQWL16Mb7/9FmvWrLFHGYmcgt5G8pUaJxfe9UFq9cQTT2PBgtkoLCzE7bePQfv2HbBq1TLs27cXa9e+o3TxnE5uUbmscUREzqShnPLDD/9hG4WIyA019tqY+YSUpta+JbVinxe5O8kzdwYOHIhffvkF+/fvx4IFCwAAjz/+OPbu3YtevXo1uiCPPvooZs+ebf770aNHceeddyImJgZ33HEHjhw5Uit+586duOGGGxATE4MpU6bgr7/+Mj9nMpnw8ssv46qrrkL//v2xfPlyGI1G8/OXLl3C1KlTERcXh8TERGzbtq3We9v6bCJLQv29ZY2TC+/6ILWKj++HHTu+xa5d32H69FkAgAceeBiff76T+aQRLpVWyhpHRORMLOWUBx98mG0UIiI31dhrY+YTUppa+5bUin1e5O6EBncOHDiAqqoq8/+npKTgjz/+wIEDB3DgwAGcOnUKqampOHDgQKMKsWvXLuzbt8/895KSEjz66KNISEjA559/jri4OEyaNAklJSUAgPT0dMybNw9PPPEEPv30UxQWFmLOnDnm1//rX//Czp07sXr1arz++uvYsWMH/vWvf5mfnzNnDoqKivDpp5/isccew/z585Geni702aQuatosLTYyCOE2kmtEgA6xkUEOKlE13vVBapKaesicT1JTDyE9PRUnT2YiNfUQUlMP4cyZ0zhyJJ35pBGa+3rJGkdEpHYiOYVtFCIi9yTl2pj5hPlETdTat6RW7PMidye0LNuECRPw008/ISQkBBMmTGgwTqPR4NixY5IKkJ+fj+XLl6N3797mx7788kvodDo8++yz0Gg0mDdvHr7//nvs3r0bo0ePxkcffYSbb74Zo0aNAgAsX74cQ4cORVZWFtq0aYMPP/wQ06ZNQ0JCAgDgmWeewWuvvYaHHnoIZ86cwd69e/Hdd98hKioKXbp0QWpqKj7++GP06dPH5meTeiRn6PFycibyrjhBh/l74xmFNkvz0GowI7ETZm0/2mDM9KHRDp8Gyrs+SE2mTp2E7du/RvPmLTB16qQG45hPpAsP0MkaR0SkdswpbKMQETVEyrXx1PHMJ8wn6qHWviW1Yp8XuTuhwZ3jx49b/H85LFu2DCNHjkRubq75sbS0NMTHx0OjqT5RaTQa9O3bF6mpqRg9ejTS0tLwyCOPmONbtWqF1q1bIy0tDd7e3jh37hz69etnfj4+Ph45OTnIzc1FWloaWrVqhaioqFrPv/POO0KfTepQs1laXXl/b5a2LKmHIgM8iZ1DsSypB1YmZ9aaFhoRoMP0odGKlKnmrg9r01R51wc5yg8/HLD4/1fSaIDQ0ADJ7+3u+SQ2MghBPp4oKKtqMCbIx5O/dSJyGbZySmPzCcCcQkTk7KRcGzOfMJ+oTWLnUExIiMLGlGxcuUCNVgPcEx+lSN+SWrEd3DQGowmpOQUozy6EzmhEbGQQBw6djOQ9dwDAYDDgP//5D95//30UFhYiLS0NRUVFkt/nl19+wcGDB/H444/XejwvLw/h4eG1HgsJCcH58+cBALm5uQ0+n5eXBwC1ng8NrT7p1Txv6bUXLlwQ+mxSnsFowvNf/W415vmvfldsibbEzqHY/sgArBnbBy/e0g1rxvbBtof7K5Z8a+76sIZ3fZBSDAYDfv75R2za9DGKiorwv/8dQXFxseT3YT6pVlppbNLzRETOzFJOYRuFiMh9NfbamPmElJacoceGg7UHdgDAaAI2HMxGcoZemYKpVKXB+m/d1vPuKjlDj6R392PypnQ8+UkqJm9KR9K7+3l8ORmhmTtXOnfuHCZOnIiCggIUFBTg+uuvx7p16/Dbb79h3bp16Natm9D7lJeXY+HChViwYAF8fHxqPVdaWgpv79rT5by9vVFRUT3zoKysrMHny8rKzH+/8jkAqKiosPnetp6XQtOIvvKa1zTmte7i4JlLKKk0WI0pqTTg4JlLuKpDCweVqjbz93fF96nkd2rrozXgMWcNf5fSiNbXhQvn8fTTT6CwsBCFhQUYNOhafPzxBzhyJB3r169nPrmCyLF38MwlVNi4aK0wGBU9N6odf+vSsc6kYX1J19ScMm/eEbZRrtDYY4/Hrjrxe1Enfi/q0NhrY+YTcezzsg+D0YSVyZlWY1btPYHrOoXwJl0Ah7LzUWJjILek0ohD2fno3665g0qlfsl/WF4RKffvFZGWJ/VAYhfOELOkqecxuc9/kgd3Fi9ejISEBCxatMi8vueqVaswb948LFmyBBs2bBB6n9WrV6NXr14YPHhwved0Ol29xFJRUWFOiA097+vrWyup6XQ68/8DgK+vb6Pfu24yFhES0rhpu019rav7bo/1JGeOO/EXRvRrZ+fS1Lf7yDk8v+MozhWUmR9rFeSDhbf1wPBerRxeHoPRhFf2/drg8xoAr+w7iTuuas8LAxv4u5TGVn0999yzGDCgvzmftGjhjzfffIP5xAKRY2/PtxlC77Un86Ii50Znwt+6dKwzaVhf0jUmp6xezZxSV1OPPR676sTvRZ34vSirsdfGzCfi2OdlH7+cuGh1WX0AuFBUjpNFlRgYHeKgUqnX0ZSzYnH6UtwS39bOpXEO7CeUh1rOY5IHdw4ePIhNmzbBw8PD/JiXlxcef/xx3H777cLvs2vXLuj1esTFxQH4Jxl9/fXXGDFiBPT62lPA9Hq9eepoRESExefDwsIQEREBoHqqac0aozXTVmueb+i11t677rRVERcvFsEkcWUwjab64GjMa93FX0XlwnF6vfSp002R/Icez1oY+T5XUIbJHx1SZOT74Jn8WgNNdZlQXb5vU7OR0DbYYeVyJvxdSiNaXwcOHMDate/j0qUSmEzAX38Vw9e3DOPH348HH7xX+POYT6qdyrss9F6n8i47/NzoLPhbl451Jg3rS7qm5BQ/vzK2Uepo7LHHY1ed+L2oE78XdWjstTHziTj2ednHibP5wnGdg7xtB7q4klKxPsKSUsf3EaoV+wmbpqnnsZrXy0Xynjs+Pj64ePFivcdPnToFf39/4ffZsGEDduzYga1bt2Lr1q1ITExEYmIitm7dipiYGPz2228w/V1DJpMJhw4dQkxMDAAgJiYGKSkp5vc6d+4czp07h5iYGERERKB169a1nk9JSUHr1q0RHh6O2NhY5OTk1FpPNCUlBbGxseb3tvbZUphMjfvTlNe6w5/YqECh+o+NCnRouaoMJrxsY+rsyr0nUGUwObRceht3fNTQF1co/t2q+Q9/l/LXl07ng7/++qte/OnTp5lP6hCp85aBYhf2LQO9FT8+1PxHtL75h3XG+lJXnTWUU9hGqY3Hruv94feizj/8XpT/09hrY+YTcfx92OdPC18vofpv4euleFnV8CchKliovhKighUvq1r+sJ+w6X+aeh6Tk+TBnbvvvhsLFizAf/7zHwDVCW7Lli147rnnMGbMGOH3iYyMRLt27cx/mjVrhmbNmqFdu3YYPnw4CgsLsWTJEmRmZmLJkiUoLS3FzTffDAAYN24ctm3bhs2bN+P48eN49tlncd1116FNmzbm519++WXs378f+/fvx8qVK3HfffcBANq0aYNBgwZh5syZOH78ODZv3oydO3finnvuAQCbn03KGxsbKbSHzNjYSEcUxyw1p0Bo6mxqToGDSlQt1F/solY0jkguo0bdgRUrXsLPP/8IwISsrDPYtWs7li17kfmkEbqGizU2ReOIiJxJQzmFbRQiIvfU2Gtj5hNSmmi/r8z9w06rb5tgBPpYX5gqyMcTfdsEO6ZAToD9hK5F8rJsU6ZMQWBgIBYtWoTS0lI8+uijCAkJwQMPPICHHnpIlkL5+/vjnXfewcKFC7Fp0yZ07doVa9euhZ+fHwAgLi4Oixcvxuuvv46CggJcc801eOGFF8yvf+ihh3Dx4kU88cQT8PDwwJgxY/DAAw+Yn1++fDnmzZuHsWPHIiwsDC+99BL69Okj9NmkPG9PLe5NiMKGg9kNxtybEAVvT8ljl02SK7hcnGicXGIjgxDu72114CkiQIfYyCAHlooIeOCBh+Hv74+XX16KsrIyzJz5JJo3b4G77x6PqVMfl+Uz3CmftPATu/ASjSMiciYN5ZSJEx9kG4WIHMZgNCE1pwDl2YXQGY2IjQzifgUKaey1MfMJKe3iZbFZFaJxrs5Dq8G8YV0wy8IWCTXmDuvCc/EV2E/oWjQmk7TJQDt37sSgQYMQHByMkpISGAwGBASoYwMhtdHrG7f+aGhoQKNe626e2fo/7DtRf4nAIdEheHlUT4eX5+OUbLzyn5M2456+riPGx0c5oET/SM7QW010y5J6ILGzY/cCcib8XUojWl/ffrsbAwYMRGBgEEpLS2EwGODv729+Pf1D5NhT8znIWfC3Lh3rTBrWl3RNySkBAf7MJ3U09tjjsatO/F7UJTlDj5XJmbU6y8L9vTEjsRPbWgpo7LUx84k49nnZB9t1jZOcoceKPX9AX1JlfiysmReeub4zz8EWsJ+w8Zp6HpO7z0vy1Ibnn38ef/31FwDAz8+PAzukiOQMvcWBHQDYd+IikjP0Fp+zp+aC66KKxskpsXMoJiREoe6NCloNMCEhiidsUsTKlcuQn38JAODr6ytpDWuqT83nICIie2NOISIl1XSS1b0LOre4ArO2H1WkferuGnttzHxCSmO7rvG02trd3BoNZ+s0JLFzKJYl9UB4naXXIgJ0HNhxMpIHdwYMGICdO3eiooLT/0gZBqMJK5Mzrcas2nsCBqNjbwMJD9DJGien5Aw9NhzMRt0qMZqADQez2dggRfTtm4Bvv/2a+UQmoc0E180VjCMicibMKUSkFIPRhJe++cNqzEvf/OHw9qm7a2z7nPmElMZ2nXQcYG+cxM6h2P7IAKwZ2wev3R2LNWP7YNvD/Tmw42Qk77lz8eJFvPXWW1izZg1atGgBna52Ivzuu+9kKxyRJak5BVbXhQSAC0XlSM0pQLwDN0zr3SoQWg3qDaBcSaupjnMk0cGwIdEhXIOUHOrSpb/w/vvr8OGH6xEc3Bze3tX5RKMBtFoN84lElUajrHFERM7EUk6pyScA2yhEZD8pWfkoKKuyGlNQVoWUrHz0b9fcQaWixrbPmU9IaQbBdZ5E41wd+7yaxkOrQULbYC6X6MQkD+6MHTsWY8eOtUdZiITobQzsSI2Ty+FzhVYvHIHqC8vD5wodOuik1sEwoqSk25GUdLvF5wICfBxcGuf39bFc4birO4TYuTRERI7VUE5hPiEiezuUnS8cx8Edx2ls+5z5hJSWmlMgHHdV+xZ2Lo36sc+L3J3kwZ3bb69OcsXFxfjzzz+h1WrRoUMH+Pr6yl44UgeD0YTUnALoiysQ6u+N2MggRUe7Q/0Fp6gKxslFrYNOai0X0c03jwAAlJRcxpkzZ6DVatC2bXv4+vpww9JGuFxhkDWOiMiZWMop7dq1R1RUmMIlIyJXJ3qXM++GdqzGtoOZT0hpPKdIwz4vcneSB3dKS0uxYMECfPXVV6iqqp567O3tjdtvvx3z58+Hlxc39HIlyRl6rEzOrDUKHu7vjRmJnRRbgzE2MgiBPp4otDL1PcjHE7GRQQ4slXoHnZr7CW7GJxhHJJeysjKsWLEE3333LQyG6gEHLy9v3HLLCLz44vPMJxLFRAZi34m/hOKIiFxNQzll9Gi2UYjIvuKigoD9WWJx5DCNbZ8zn5DSeE6RRq19cUSOopX6gueeew7Hjx/He++9h5SUFBw4cABr1qzBwYMHsXTpUnuUkRSi5g3J1LhKZmxkEMJtJIuIAJ3DB52MgrdziMYRyWX58iXIzMzAqlWr8fXX+/DVV3uxbNkqpKb+xnzSCB1C/GSNIyJyJpZyyvLlq9hGISJyU71bBdrsN9Cg/p47zCekNPbhSKPWvjgiR5E8uJOcnIz/+7//w4ABA9CsWTMEBATg6quvxksvvYSdO3fao4ykANENyQy2FrG1g9ScAqENK0XXKZWLh1aDGYmdrMZMHxrt8CXtpKzXqiSD0YSUrHx8fSwXKVn5ihxb5Fg//vg95s5dhL59E+Dn5wd/f3/06zcAc+cuYD5phK+PC+65IxhHRORMGsopbKMQkb05S3vL3aTmFMBWi9KE+t8L8wkp7atjF2SNc3Vq7YsjchTJy7KFhITg4sWL9R6vqKiAv7+/LIUi5al5QzI1r6eZ2DkUQ6JDsO9E/d/IkOgQRZayc4b1WpMz9Hj5uwzkXa40PxbWzAvPXN9ZseX/yP6aN2+OS5fqLyNWWcl80hjnCspljSMiciYN5RS2UYjI3pyhveWODmXnC8f1b9fc/HfmE1Ia23XSqbEvjshRJA/uTJo0CfPmzcOkSZMQFxcHT09PHDt2DK+//jpuv/12HDhwwBzbr18/WQtLjqPmARQ1r6f5+r6TFpMJAOw7cRGv7zuJaUM6OrRMfaOCsF5gvda+Cq3XWrP8X115lysxa/tRLEvqwUTsoiZMeBD/938vYMKEB9CrVww8PT2RkfE73nvvHdxxx2jmE4laBuiQhiKhOCIiV2Mpp2Rm/o7169eyjUJEdpXQJliovZXg4Jsi3Z3R2Lg45hNSGtt10qmxL47IUSQP7syfPx8A8OKLL9Z77s0338Sbb74JANBoNDh27FgTi0dKUfMASu9WgdBqAGurdmk19dfOtbeKKiM+OphtNeajg9mYfE17eHtKXhGx0TQasamnonFyMhhNWPLNH1ZjXvrmDwyJDuEUWhe0bFl1Hnn11ZfrPcd8Il27Fr6yxhERORPmFCJSSozgPg6icSQPHy+x9mPdOOYTUlrHUD/gd8E4QkWVERtTrPfFbUxxfF8ckaNIHtw5fvy4PcpBKlOzIZm1pdmU2pDs8LlCqwM7QPXAz+FzhQ5dMm7TbzlCa/pu+i0H9/Zr44giAQDyisWm6orGyelQVj4KBfZPOpSVj35XTJUn1/DDDwcsPq7RAKGhAQ4ujfNL/kMvHPfI1R3sXBoiIseylFOYT4jIEX4TXP7rt+x8DGjfwr6FIbMDZ/KF4yZe9c/fmU9IaX/kXpY1ztV9lnZWqI/ws7SzGB8f5ZhCETlQo4YsT5w4gaKi6imCP/zwA55//nls3rxZ1oKRstS8IZlal4xLOyu2QaZonFyOnLM9nVdKnJwOZuXLGkfO5/TpP1FcXAwA2L//F6xcuQw7dmxVtlBOKiu/VNY4IiJnYymnsI1CRPa266jYpuaicSSPM5fErnktxTGfkJJScwpljXN12fllssYRORvJgzuffvopkpKScOzYMRw9ehSPPfYYsrKy8Nprr+G1116zRxlJIYmdQ7EsqQfC6yy9FhGgU3QfFLUuGacTnN4pGicXk+DOnaJxchJdCU6BFePIAbZt+xz33XcXMjJ+xx9/HMfs2dNx9mwO3n33beaTRtBC7IciGkdE5EwayilsoxCRvZVWGmSNI3n4eXk0Ko75hJRmMoltGCUa5+qign1kjSNyNpJ7mdetW4dly5ahf//+2LJlC7p3745169bhlVde4Z0MLiixcyi2PzIAa8b2wYu3dMOasX2w7eH+im5wX7NknDVKLBnXNcxf1jjZiPbjKtDf2zcqWNY4ci4ff/wh5s9/HnFx8di1azs6deqClStfx+LFS5lPGiE8wEvWOCIiZ9JQTmEbhYjsLaa14J47gnEkj8hAsZs968Yxn5DSAn3EdtAQjXN1Y2Jaw9aiQlpNdRyRK5I8uHPhwgXEx8cDAPbu3YsbbrgBANCyZUtcvsz1Hl2Rh1aD+DbBuKl7OOLbBCu+sb2HVoObuoVbjRnWNczh5Qz118kaJxd/b7GELxonp/g2wQiycUES5OPp0L2TyHHy8vLQp08sAOCnn37AtddeBwAICwtnPmmENs3FNtQUjSMiciYN5RS2UYjI3sbGRcoaR/Lw8BBr39aNYz4hpUUF+8oa5+q8PbUY3DHEaszgjiHwdvAqOkSOIrk3t2PHjtixYwdatGiBs2fP4oYbbkBlZSXWr1+Pbt262aOMbsNgNCE1pwDl2YXQGY2IjQxSfCBFjQxGE7YfOW81ZvuR85gyuIND6y/IV+znJBonF08PsToQjZOTh1aDucO6YNb2ow3GzB3Whb8DF9WuXTt8881uNG/eHBcunMfgwdehqqoKn3yykfmkEXy9xC5WReOIiJxJQzmFbRQisjcPrQbeHlpUGBpeIknnoWWbxsF8vMTqu24c8wkprbFLCrorg9GEYxes7yF9PLcYBqOJ52FySZJ7mWfNmoWnnnoKBQUFGD9+PKKjo7F48WJ8++23WLNmjT3K6BaSM/RYmZyJ3OIK82Ph/t6YkdhJ0SXQ1CglKx8FZVVWYwrKqpCSlY/+7Zo7qFTAvgy9cNzVHazfVSCnvlHBeA9ZQnFKqNnbqe7xH+Gvw/TEaB7/LuyJJ57GggWzUVhYiNtvH4P27Ttg1apl2LdvL9aufUfp4jmdcwXlssYRETmThnLKDz/8h20UIrKrlKx8qwM7AFBuMDq8feruLpeL7UdSN475hJR2uULw2BWMc3WpOQW1+pIsuVBUjtScAq4KQy5JaHDn9ddfx4MPPoiAgAC0a9cOv/zyC4qKihAUVL1m7OOPP445c+bAy4vr+DdGcobe4syF3OIKzNp+FMuSerCD+wqHsvOF4xx58XzsQrGscXKJjQyCBoDJSozm7zilJHYOxZDoEKTmFEBfXIFQf2/OXHNR7733Du666x74+/sjMrINduz4FsXFxQgMDAQAPPDAw3jyyRlo2ZINX6nOFokN2ojGERGpna2c8uCDD2Px4oVsoxCRXam1feru9CXWO3uvjGM+ITU5k18qa5yr09sY2JEaR+RshNZmee+991BQUAAAuP7665Gfn28e2AGA0NBQJrlGMhhNWJmcaTVm1d4TMBitdc27F6PgzQmicXIJ0IlNiRWNk8vhc4VWB3aA6oGfw+cKHVGcBqltbyeyj48//hBFRdXH2tixSSgoKDA3mgCgRYsQeHpyY8jGMNq4Y1RqHBGR2onkFLZRiMjeRNvqbNM7mISOA+YTUpOKSusr1UiNc3Wh/t6yxhE5G6EetPbt22Pq1Kno1q0bTCYTXnzxReh0ljeFX7p0qawFdHXOMH2wZi8gtcyoCBTcs0Y0Ti4J7Zrj1yzbAyQJDr5b63xhmaxxRE3Rpk07zJs3E506dYHJZMKrr66ol080GkCn82I+kcjP2wP5AstP+HlzbWYicg22ckpNPgHYRiHXw/1a1SPQR7B9KhhH8vDTidW3n86T+YRURfRcznN+td6tAoVWq+ndKtBKBJHzEsp2b7zxBj766CMUFVVvUGUy8Y4Tuah9+qAa9wIK8RMbbReNk8vlcoOscXI5fFZsRs7hs4W4tWdLO5eG3N2SJcuxZcunKC6uWZ6wfj5himmcYsFzi2gcEZHa2copzCfkqtTYRnNnBaVid8+LxpE8CkoqheNWMZ+QiohupcMtd6ql5RQIrVaTllOAflwak1yQ0OBO27ZtMXfuXPPf582bB39/f7sVyp2oefqgWvcCCm0mWGeCcXI5Xyi2j4VonFzyLosNDIrGETVFZGQUpk2bYf77U089Az+/ZrViNBogNDTA0UVzelWCrU7ROCIitbOVU5hPyBWptY3mznKLxdp3onEkD6PN7t5/4phPSE08BSfkiMa5ugNn8oXjOLhDrkjyvODRo0fj2LFjDT7fr1+/JhXI3cRGBiHc39vq0mwRATqHb3YvuhfQkOgQh08FLS4Xu+NJNE4uF0vELtZF4+TSzFvsZy4aRySXW265DX/88Xu9xzUaICjIj/lEIpPgOu6icUREzsRSTqnJJwDbKOQa1NxGc2fN/cT2YhGNI3lUVolNa6gbx3xCSvPzEjt/i8a5urMFpbLGETkbyb25EyZMsPi4t7c3wsLC8N133zW5UO7EQ6vBjMROFu++qjF9aLTDL87VvBfQ69+fFI4b2iXMzqX5x1+Cd2KJxsnllh7h+OpYrlAckSNNnTrJ4uNeXt4ID2c+kapUcLU10TgiImfSUE5hG4VciZrbaO7s55N/Ccc9fZ1di0JXKBMc3Kkbx3xiP9wrTExOgdiqKqJxru6vErF6EI1zN/xdOj/JgzvHjx+v9XeDwYAzZ87ghRdewG233SZbwdxJYudQLEvqUW/d5IgAHaYPjVZkWn1ukeDUcsE4Oam2bBrBk59onEz6tW0OPy8PlFQ23KPr5+WBfm05PZUc64cfDtT6u8FgQE5ONl55ZTnuuON2hUpFRETOyFJOOXs2G6tXr2IbhVyG2vdrdVeXSsX2dhGNI3lUGMRmq9eNYz6xD+4VJq5ScC8d0ThXVy44kCsa5074u3QN2qa+gYeHBzp06IDZs2fjtddek6NMbimxcyi2PzIAa8b2wWt3x2LN2D7Y9nB/xX5Mar5A9fIQO2xF4+TSOUxsHyrROLl4aDXo1zbYaky/tsGKj8wbjCakZOXj62O5SMnKh4FLR7kdDw8PtG3bDtOmPc18QkRETVKTU9hGIVei5v1a3Vmgj9hya6JxJA+dl4csccwnTVezV1jdmYc1e4UlZ+gVKpk6iXZlObjLS7VaB/nKGucu+Lt0HbKdCi5evIjCwkJJrzl9+jQeeughxMXF4brrrsO6devMz2VlZeGBBx5AbGwsbrnlFvz444+1Xvvzzz9jxIgRiImJwX333YesrKxaz7///vsYPHgw4uLiMHfuXJSW/rO2Ynl5OebOnYuEhAQMGjQI69evr/VaW59tLx5aDRLaBmNkbCQSFO5sb+4ruG6wYJycEruGyBonlxu7ii1rJhonl4oqI74/cdFqzPcnLqJCwbsYkjP0SHp3PyZvSsf8L49j8qZ0JL27n8nETV26dElyPgGYU9oHiU3GFY0jInIFbKOQK4mNDEKgj/U8HuTj6fD9Wt3dE9e2kzWO5NE2WCdrHPNJ44juFcabO//RLcJP1jhXd2vPCFnj3AF/l65Fcg/PnDlz6j12+fJl/Pzzzxg+fLjw+xiNRjz66KPo3bs3vvjiC5w+fRrTp09HREQERowYgSlTpqBLly7YsmUL9uzZgyeeeAJffvklWrdujbNnz2LKlCmYOnUqBg8ejDfffBOPP/44tm/fDo1Gg6+//hqrV6/GihUrEBISgjlz5mDFihVYsGABAGD58uU4cuQIPvjgA5w9exazZs1C69atMXz4cJhMJquf7S7CA8QucETj5DRzaBfsOJInFOdIP5+yPoByZdwQB87I2pSaA1unY9PfcfcmtHFEkWqpuVugrpq7BZYl9eB0UBf10kvP13uspKQEBw/ul5RPAOYUADAIjs+KxhERORNLOaW0tAQHD/7KNgq5FK6Crz7n8sWWwRONI3n4eordy1w3jvlEXtwrTLpAb7GuWtE4V9c3KhgawGq/l+bvOKrG36VrkeVMEBwcjFmzZmHkyJHCr9Hr9ejevTsWLVoEf39/tG/fHgMHDkRKSgpCQ0ORlZWFTz75BH5+foiOjsYvv/yCLVu2YOrUqdi8eTN69eqFiRMnAgCWLl2Ka665Br/++isGDBiADz/8EPfffz+GDh0KAHj++efx0EMPYebMmTCZTNi8eTPeffdd9OzZEz179kRGRgY2btyI4cOH47///a/Vz3YXsZFBCPf3tvpjjwjQKXJXmK+3B4ZEh2CfldkoQ6JD4OstNg1bLkcvFMkaJ5dDZ/KF4xw9uCN6t8CQ6BDFl40jxwgKCsITTzyFe+65S9LrmFMAfUmVrHFERM4uMDCIbRRyKak5BSgos57HC8qq2BnjYGculcgaR/LQXxa8NhaIYz5pPO4VJp2tTnepca7u8LlCoRuaD58rZG78G3+XrkXy4M7SpUtl+eDw8HC8+uqrAACTyYRDhw7hwIEDWLhwIdLS0tCjRw/4+f0zxTA+Ph6pqakAgLS0NCQkJJif8/X1Rc+ePZGamoqEhAQcPnwYTzzxhPn52NhYVFZW4vjx4zCZTKiqqkJcXFyt916zZg2MRqPNz3YXHloNZiR2sjijosb0odGKdbi3bW59rUxbz9uHaF04ts7+vFRqO0hCnJx4t4B7mzt3ocXHNRrA21vaWvHMKUCF4Iwc0TgiImdiKadoNEBoaICk92E+ITVjZ4w6ZV4UG7QRjSN5lAguO143jvlEXtwrTLqzRWLncNE4V8fcKB1/l65F8uCOyWTCd999h4yMDBgMBvPjFRUVOHr0aK01REUlJibi7NmzGDp0KG666Sa89NJLCA+vvS9JSEgIzp8/DwDIy8tr8PnCwkKUl5fXet7T0xPBwcE4f/48tFotmjdvXqvjMDQ0FOXl5cjPz7f63lJpGtGHX/OaxrxWbtd3CcXypB54OTmzVgd8RIAOM4ZGI7GLMktlVVQZseFgttWYDQez8dig9vAWnIoth/g2wTiee1kozpHfr6+X4HR0L63Djzv9ZcEkfLlC0d+Emn6XzkC0vkwmE374YR9OnToBg3mtMBMqKytx6lRmo/IJ4Jo5ReTY8/bQoLTK9pq43h4aHssN4G9dOtaZNKwv6ZqaUzw9NWyjXKGxxx6PXXWQ0hnD78pxPG3eM/5PHL8Xx2nb3AdZ+WVCcVd+L8wn4kSO57gosVVh4qKC+Pv4m+gaNB5gXgaYGxsjLqp6D79CK7OBg3w8+btsQFOvi+WuU8mDOy+88AI+++wz9OjRA+np6YiLi8OZM2eg1+sxbty4RhXi9ddfh16vx6JFi7B06VKUlpbWu2vb29sbFRXVycDa82VlZea/W3reZDJZfA6oHqCy9dlShIRIu7NDrtfKaWxoAO64qj1+PfUXcovKEB7gg/4dWii6RNY7+6wv41Vjx+95mDSkk51L8w+Np1gK1nh6SL7rpylE9z8zmqTfjdRU0a3FflfRrYMdXjZL1PK7dBa26mvx4sWy5xPANXOKyLFXLjCwUxOnht+TmvG3Lh3rTBrWl3RK5BR3zSf2fD01zY0t/NHq6z9wvhpV1jsAAQAASURBVKDM4nCCBkDLIB/cGBvFJY0d6ExBuXAcr8Ecx1twPxJvb89a3wvziTjRnLB4VC889tEhALX3Rak5Sz0/siciwgMlf76ruiy41MLlCiPPKWBubAyD0QStjbrQajUIDQ1gnVmhlutiyYM7X375JV5++WUMGzYMw4cPx6JFi9ChQwfMnj0blZWVjSpE7969AQDl5eV45plncMcdd6C0tPYSURUVFfDx8QEA6HS6eomnoqICgYGB0Ol05r/Xfd7X1xcGg8HicwDg4+MDnU6H/Pz8Bj9biosXi2AS7FivodFUHxyNea09dQ7yRueg6guAS38VK1qWL9POCcfd0TPCzqX5R1mZ2PFfVlYJvd5x++5oNWIHklZjcmi5AKBdM09oNdYHoLSa6jhHl+1Kav1dqpVofe3atQsLFryA665LxLhxd+DJJ2eibdt2WLLk+UbnE8A1c4rIsSe62poRUPT3pGb8rUvHOpOG9SVdU3JKu3btsGLFErZRrtDYY4/Hrno8PaQjnm1g6WzT388r3V5zN5UGsauwSoOR12AOlFcgtux4XkFpre+F+UScaE5IaOmPZRZWhQn/e1WYhJb+/G1cge066ZgbpTl4Jh/5JdbPZ5dKKvFtajYS2gY7plBOpKnXxTWvl4vkwZ3i4mL06tULANClSxekp6ejc+fOmDRpEh566CHh99Hr9UhNTcUNN9xgfqxTp06orKxEWFgYTp48WS++ZupoREQE9Hp9vee7d++O4OBg6HQ66PV6REdHAwCqqqqQn5+PsLAwmEwmXLp0CVVVVfD0rP7n5+XlwcfHB4GBgYiIiEBmZmaDny2FyYRGN36a8lq5GYwmpOYUQF9cgVB/b8RGBjnNyK0j67BlgE44zpHlCtR5AbB9YRuo83L4MZd+ttDmzCKjqTpODXvuqOl36Qxs1dfly5fRtWsPmExAx46dcPTo/9ChQzQmTHgAzzwzTdJnuXpOETn2PAAYrIeY43gcW8ffunSsM2lYX9I1Jqd07BjNNkodTT32eOwqb2jnUCxL6oGVFpbOnj40GkM7h/I7crAAb08UlNm+Cgvw9uR340BSZj9c+b0wn4iTkhOGdg7FtdEhSM0pQLlWC53RaO5b4u+iNk8NUClQJ54a5uQaQzuHYkh0CPaduFjvuSHRIcyNdUjZp4j11jC1XBdL3pCkTZs2OHq0ejS0c+fOSE9PB1C9LmlRkfiIcXZ2Np544glcuHDB/NiRI0fQokULxMfH43//+595uikApKSkICYmBgAQExODlJQU83OlpaU4evQoYmJioNVq0bt371rPp6amwtPTE926dUP37t3h6elZa7O4lJQU9O7dG1qtFjExMVY/290kZ+iR9O5+TN6UjvlfHsfkTelIenc/kjP0tl9sJ4M6tJA1Ti7Zl2zvtyMlTi6RQWJ34IjGyYkb37m31q0jkZFxHADQoUNHHDv2v7+fkZZPAOYUABDcXks4jojImTSUU9hGIVeU2DkU2x8ZgDVj++C1u2OxZmwfbHu4PxI7K7MnqruLaS12961oHMmjokpscKduHPMJKU1wRUHhOHfw+r6TFgd2AGDfiYt4fd9Ji8+5Kyn7FJH6Se7imThxImbOnIkvv/wSt9xyC7Zu3YoXXngBs2fPRt++fYXfp3fv3ujZsyfmzp2LzMxM7Nu3DytWrMDkyZPRv39/tGrVCnPmzEFGRgbWrl2L9PR0jBkzBgBwxx134NChQ1i7di0yMjIwZ84cREVFYcCAAQCA8ePH47333sOePXuQnp6ORYsWYezYsfD19YWvry9GjRqFRYsWIT09HXv27MH69etx3333AYDNz3YnyRl6zNp+tN7Gd7nFFZi1/ahiAzwardiwqGicXFKyxS70ROPk8lep2NRx0Tg5MaG4t7vvvheLFz+H7777BtdfPwxffbUTr7yyHC++uEhSPgGYUwCgTHD+vmgcEZEzsZRTVq1azjYKuSwPrQYJbYMxMjYSCW2DnWZlBVd0NFdsqR/ROJJHWZXInPb6ccwn9nHljcNPfpKqihuH1crGalmS41xdRZURG1OyrcZsTMkWHvB1B71bBcLWZYNWUx1H6qcxmaRPIDpw4AD8/PzQs2dP/PDDD9i8eTOCg4Mxbdo0hIaK3y104cIFvPDCC/jll1/g6+uLe++9F5MmTYJGo8Hp06cxb948pKWloV27dpg7dy6uvvpq82v37duHl156CefPn0dcXBxeeOEFtGnTxvz82rVr8f7776OiogLDhg3DwoULzWuTlpaWYtGiRfjmm2/g7++Phx56CA888ID5tbY+W5Re37g9d0JDAxr1WjkZjCYkvbu/3sDOlSICdNj2cH+HNySe2XoE+078ZTNuSHQLvDyqlwNKVC1x9U8oKheYjq/zQPIT1zigRNUe35SGA1kFNuP6tQnCW2Mde7eOmo+zK6nld+kspNRXauoh+Pr6oWvXbti//xfs2LEVQUFBePbZGZLyCeDaOUWkLvut/F74/Q7MuFbS57sL/talY51Jw/qSrik5ZefOrQgPD2Ub5QqNPfZ47KoTvxd1uPHNn5AvsCxbsI8Hvp3iuHaguxv6+g8oFljbyt9Lg73TBtd6jPlEjOi5p+bG4YYsS+rBmYdXYLtOmo9TsvHKf2zPzHn6uo4YHx/lgBKpX0pWPiZvSrcZt2ZsH1VskaA2Tb3+qnm9bOWROrhz/vx5tGzZst7jBoMBGzZsqJUw3J0zD+6o+Yf+3K5j2H08z2bc8G5heOHW7g4o0d+f99ZPuFhq+6I+xNcDux933EX9/F1H8fVx23fD3NQtFC/e2sMBJarNGS701PK7dBai9ZWbewHh4RH1HjcaDfjqq63MJ1fg4I5j8LcuHetMGtaXdE3JKRoN0Ly5H9soV+Dgjmvh96IOt639BeeLbN9C3zLACzseHeiAEhEAXP/GjygU2Hcn0FuL76YOMv+d+UScyLnHWW7oVJOBq75HleCeO79MZ7tu+XeZ2Jx61mbcnbGt8ez1nRxQIvX7+lgu5n953Gbci7d0w03dpe/H5erUNrgjeVm28ePH488//6z12MGDB3H77bdj9erVcpWLFJZbVC5rnJw6hfnJGieX5r5essbJpWWA2F46onFyS+wcigkJUfWmhGo1wISEKMUHdsh+Hn/8YWRlnan1WFpaKiZOvJf5pBFEm0JsMhGRK2oop7CNQkT25i+4oaFoHMmjuZ9g+7xOHPOJvFJzCqwO7ADAhaJypObYXm3EXTQT7DISjXN1EQFiy/iLxrkDbpHgWiRfXdx4440YP348jh49iosXL2LmzJm477770LNnT+zevdseZSQFXBLcf0U0Tk7FAkufSYmTS5ng+p2icXLx13nIGie35Aw9NhzMhrHOaLfRBGw4mM01eF3YkCFD8fjjD+OPP47j0qW/8MILz2HatEno0qUb80kjiN4wwht7icgVWcopU6dOYhuFiOxOZGluKXEkD41G7JamunHMJ/LS2xjYkRrnDkyCt+OJxrm6s/mlssa5g9jIIITbGLiJCNAhNjLIQSWipvCU+oI5c+agZcuWuO+++6DVatGhQwd88skn6NOnjz3KRwpR6ywUACg3iF0Ui8bJpbhcbKBLNE4umXmXZY2Tk8FowsrkTKsxq/aewJDoEE7RdkFTp05HWFg4pk2bDI1Gi7Zt2+Htt99Dz569ZJ2iSkRErs9STlmz5j1cey2XQCIi++LgjjoZBPsD6sYxn8irsTOo3Fm5wF5RUuJcXdYlsUEb0Th34KHVYEZiJ6tbJEwfGs1+OCfRqHnBDz74IBYvXoyKigo8/PDDHNhxQSHNxKbeicbJae8fYjM5ROPkUlQhllhF4+RyrlBs6TzRODlxijbdffe9mDlzHiorKzB+/H3o0aOX0kUiIiInxZxCREooE9kcQ0IcyeOswD5IDcUxn8iHS0dLVy54qhCNc3UXBVcUEo1zF4mdQ7EsqUe9GTwRATpV7H1N4oRm7nTr1s3ilFaTyYRp06bVeuzYsWPylIwUpeYEXFBWJWucbFS6JlKF4DJwonFy4hRt9zN4cL8G88lzz82q9RjzCRERWcOcQkRqINqKcnxry73VXfbbWhzzif38VSLWoS4aR1RXcx+xRalE49xJYudQDIkOQWpOAcq1WuiMRsRGBnHGjpMROrI//PBD8/+bTCbhtUvJeak5Aft7e6K00vbn+ns79sQtOsne0ZPxw/y9cDxPLM7RWghOvRaNI/V7/fU15v9vKJ9oNEBQkJ8ji0VERE7IVk5hPiEiIhHMJ/bDjdvJ3i4J3tgtGuduPLQaJLQNRmhoAPT6Ipg4I8zpCPV+9+/f3/z/o0ePxtKlS9G1a1e7FYqUp+YEPDOxE57dYftumZmJnRxQmn9oIDYpx9FDo2EBOlnj5KTSyU5kR3Fx8eb/nzjxXsybtwjR0bV/qxoNuOcOERHZZCunMJ8QkSNoITYrp1Fr4lOjhTXzRO5l2525Yc08mU/sqHerQGg11mdSaTXVcUSN0cLXEycF44hckeTri9zcXHh4eNijLKQisZFB9dZdrCsiQIfYyCAHlegf13QMkTVOLqKzFh09u7GZ4Awm0Tg5XRKc+SUaR87l4kU9tFo2c4mIqOmYU4hIKR6C7TvROJJHRKBvo+KYT+R1+FyhzSXyjKbqOKrmJXj4ica5Oj/BvizROCJnI/nIHjVqFB5++GEkJSUhMjISOp2u3vPk/Dy0GsxI7IRZ2482GDN9aLQi6zD+lp0vHDegfQv7FuYKwT4euFhqe9G1YB/HDo7mXRbbr0Y0Tk5qniFG9jd8+K2YMWMqbrrpFrRs2Qre3tXfs0YDBAT4Mp9IpNbZg0REjmApp9TkE4BtFCKyH63gRRi3MHCs6FA/HD5XJBR3JeYTeXGfXem8tUClwHRAbw7uAACimvsCuCQYR+R6JA/ufPnll9Bqtdi5c2e95zQaDROdC0nsHIplST3w8ncZyLv8z8yJcH9vzEjshMTOoYqUa9fRC8Jxjhzc0QguTCkaJxeT4E6SonFyqpkhlmvlQk6pGWJkf8nJ38LDwwN79nxd7zkPDy3ziURc5pCI3FlDOUWr1bCNQi7JYDRVb4CcXcgNkBUm0gkrJY7kEaAT6+6qG8d8Ii/e0CmdaJcR90aplpF7WdY4ImcjeXAnOTnZHuUgOM8FuknhDFJaaXt2jJQ4uRRViF2ti8bJRXTMRoGxHVXPECP727x5u8XHuaY1ERFJZSmnMJ+Qq0rO0GNlcmatG6SUvgHPnYm27ji241j6y2JLe9eNYz6RV48IsXoTjXMH5YInC9E4V1cm2PcnGkfkbBo1ia+oqAgbN27EkiVL8Ndff2Hv3r3IysqSu2xuJTlDj6R392PypnQ8+UkqJm9KR9K7+5GcoVe0TLO2H601awcA8i5XYtb2o4qVTXSjPUdvyKfWBHzxcpmscXJL7ByKCQlR9ZYp0GqACQlRbKC6uOLiYmzZsgmvvbYS+fn5+OmnH5CTk610sYiIyAlZyilso5CrqWmj1Z35nltcoWgbjUhtmvuJ3ctsKY75RD5fHD4na5w7MAjeeCsa5+rKq8QGbUTjiJyN5MGdP/74A8OGDcOWLVvw73//G5cvX8Y333yDpKQk/Prrr/Yoo8tT4wW6wWjCkm/+sBrz0jd/wKDAdI9Oof6yxrm6U3+Vyhont+QMPTYczK43c8hoAjYczGYD1YWdPJmJu+++HV9+uQNffLEZly8XY9++ZNx//3jmEyIikqShnMI2CrkSg9GElcmZVmNW7T2hSBuNSG0Ony1sVBzzibyyLon1M4jGEdXl7SXWtS0aR+RsJB/ZL774IsaNG4fPP/8cXl5eAIClS5di/PjxWL58uewFdHVqvUA/lJWPwrIqqzEFZVU4lJXvmAJdIf1cgaxxchH9MTk6nZQJLu4sGicntR7/5Bivvvoybr99DN57bwO8vKrXWJ47dyFGjx7DfEJERJI0lFPYRiFXkppTYHWvSgC4UFSO1BzHtoOI1Ki4XOwu/bpxzCdEzsXH00PWOCJnI7mf+fDhwxY3kLv77ruRmWm9k5bqU+sF+kHBQRvRODkZBccgROPk4iG4LYxonFzUWi5Avcc/OcaxY0cxfPit9R4fOXI08wkREUnSUE5hG4Vcid7GdbPUOCJXVlJh/WbVhuKYT+TVo6XgnjuCcUR1iXZlcSdnclVii5BeoUWLFjh16hTatm1b6/FDhw4hJCREtoK5C7VeoGsEz3qicXLy8RQbkxSNk0ul4OQS0Ti5tPDzQnGB7eOnhZ+XA0pTW25Ruaxx9lBRZcRnaWdxsdyAEJ0HxsS0hreDjy1XFRzcHGfOnEZkZFStx48cSWc+IXICPD+SmjSUU9hGIVcS5CvWfBeNI3JllVVid3vWjWM+kVdRudggm2gcUV1q7SMkchShq77KykrzEmyPPPII5s+fj8mTJ8NkMuG///0vvvjiC3zwwQd4+umn7VpYVxTq7y1rnFxiI4MA2N4wsDrOsfb8kSscN3FgOzuXRv3CAnQ4IzC4Exagc0BpartUWilrnNxe33cSG1Nq7wf02r6TuCc+CtOGdFSkTM6uqqoKnp7Vqeeee+7DsmUvYsKEB2EyGXHo0EHs3r0LmzZ9jOnTpytcUiKyhudHUgORnLJ587/ZRiGXcSLvsnDcVe1b2Lk0ROp2uVJsWbbLlQbmEzsK8hEclBaMI6rLJHjXuWgckbMROntec801GD58OEaMGIG7774bERERWLduHXx8fLB8+XJ06NABL7zwAm655RZ7l9flxEYGIdzf2+rSVBEBOocPongInvRE4+SUnV8ma5yr0wp+R6JxcmruKzZbSDROTq/vO4kNB7PrPW40wfw4OzClu+22YRg69HrceONwjBp1B8LCwvHxxx/Cx8cHb775Gtq2bYdZs+bjrrtGK11UImoAz4+kFiI5hW0UciXZBYLtIME4IlcmOLaDSgPziT0V2NjLWWocUT0mwb4s0TgiJyM0uDN//nzs3r0bDz/8MJo3b45bbrkF8+bNQ48ePexdPpfnodVgRmInzNp+tMGY6UOj4aF17Ekot1hwuSzBODmJVoWDq0y1SgWvakXj5BQuOFtINE4uFVVGbEyp33F5pY0p2Zh8TXsuQSTR00/PxN69ezBjxjQEBwcjMfFGPPnkDHTp0s0cwxtqiNSL50dSE1s5RaMBQkO5hj+5jqoqsc5P0TgiV+apBSoEVmbz1DKf2JOab+gk11BaIbbSi2gckTUGowmpOQUozy6EzmhEbGSQw/vs6xIa3ElKSkJSUhKKi4uxZ88e7N69G3fddRfatGmDESNG4LbbbkObNm3sXVaXldg5FBMSouotb6LVAPfERyGxc6jDy3TkXJFw3K09W9q5NLW1CtQh86Ltu9FaBTp+mTE1ulQiuPSZYJyc1Dpz7bO0s7V+i5YYTdVx4+OjrAdSLcOG3Yxhw25GScllfP/9f7B37x5MnjwRrVtH4oYbbsKNNw5HVBTrlEiteH4kNbGVU4YNG47Q0O5KF5NINsdyxZZlE40jcmUtA71xJt/28uQtA70xbNi1zCd2otYbOsl1cF+nplHjYIVaJWfosTI5s1YfZri/N2YkdlKk776GpEUt/f39MWrUKIwaNQrFxcX49ttvsXv3bqxZswZdu3bFbbfdhvvuu89eZXVZyRl6q8ub9God6PCDxGSy0XMjMU5OQb7eAGwP7lTHOY4GgEhtOPoUqebBHbXOXOPSf/bn59cMw4ffiuHDb8Xly8XmRtSHH/4LnTp1wu23j2I+IVIhnh9JjazllG7d2EYh11EkuGyRaByRK4sO9ceZ/L+E4mown8ivd6tAm30lmr/jiBqjtEqsX1I0zp2odbBCjZIz9Bb7LnOLKzBr+1EsS+qhWJ01er0Mf39/3H777XjnnXewdu1aVFVVYenSpXKWzS0YjCasTM60GrNq7wkYbN0mKzON4LpIonFyaqYTG5MUjXN1VYLHjmic3BI7h2JZUg+ENas9DTvc31uxk2NUsI+scWRds2b+uPnmEVi+/FW8/PJrzCdEKsbzI6kdcwq5Mh9vsea7aByRK9NfFltCvqE45hN5HMrOt3kTrOnvOKLGaCU460s0zl3UDFbUXUmnZrAiOUOvUMnUR6199zUa1fttMplw4MABfPPNN9izZw9KSkpwww03YObMmXKXz+Wl5hRYXZIKAC4UlSM1pwDxbYIdUygAvVoF4LO0c0JxjtandSC+P2H7Dpw+rR1754foT9jRP3WTwDrDUuLsRYmBwoaMiWmN1/adtLr0kFZTHUdNYzKZkJp6CPv2JeP77/+D0tJSDBlyHebMma100YjIAp4fSc0s5ZRhw25kG4VcRq+WgTgpsDx1r5a8A54ov0RsBpulOOYT+Xx5NFc47qr2LexcGnJFY2Jb49esAqE4qiY6WDEkOoRLtEG9ffc1hAd3qqqq8PPPP+Pbb7/Fd999h5KSEgwZMgTz58/HtddeC29vxy6B5Sr0Ng4OqXFyaRkodsetaJy81DqMok4mwfXiTAqdr9U4tdHbU4t74qMsLpdY4574KG4W3khVVVU4ePBX7Nu3Fz/+uA+lpSUYOHAQnnpqJgYOvAbe3l7csJRIpXh+JLWxllOuvvoatGrFjiJyHfmCy62JxhG5Mj9vD0lxzCf2UVJhkDWOqK79py8Jxw3tEmbn0jgHtQ9WqI1a++5rCA3uzJw5E/v27UNJSQkGDhyIZ599FjfeeCOaNWtm7/K5vFB/sUEx0Ti5xEYGwc9Li5LKhqdz+HlpHb7RPQCkZtseka+Ju7+/nQvjBDy0QJXAdZKHAv1war5bYNqQjgCAjSnZte5Q12qqOy5rnidpXnjhOfz8808oLS1BQkJ/TJnyJK69dij8/PyULhoRCeL5kdTCVk5R0aRgp8aNdtUjxFfs3kzROCJXFh6gw+95JUJxzCf207NVM+w7cVEojqgxzlyy/TuXEucO1D5YoTZq7buvIXTVd/bsWTz11FMYPnw4WrTg3Qpyio0MQri/t9UR04gAncMHUQxGk9WBHQAoqTTCYDQ5vHF3+q9SWeNcnoonOqn9boFpQzpi8jXt8VnaWVwsNyBE54ExMa15R3oTnD9/Ho8++jiGDr0BwcHBSheHiBqJ50dSA+YU++NGu+pysVRsRo5oHJErax/iix9O2r6jv32IL35nPrGb8wViex+JxhHVVW4Q68wSjXMHah+sUBu19t3XEGqBb9y4EePHj5d9YOfChQuYNm0a+vfvj8GDB2Pp0qUoL68+oWdlZeGBBx5AbGwsbrnlFvz444+1Xvvzzz9jxIgRiImJwX333YesrKxaz7///vsYPHgw4uLiMHfuXJSW/tPRX15ejrlz5yIhIQGDBg3C+vXra73W1mfLyUOrwYzETlZjpg+NdvgAyqeHGl5upTFxciqrEtscRjTO1YneZaTE3UjOcLeAt6cW9yREYfHIXrgngUsNNdWbb76L228fI3ujifmEyPF4fiSlMafYN6dwo131CfHzkjWOyJVpINbA1UDDfGLHfJKdb3ufMClxRHW1DfaVNc4d1AxWWKPkYIXaqLXvvoZirXCTyYRp06ahtLQUGzduxCuvvIK9e/fi1VdfhclkwpQpUxAaGootW7Zg5MiReOKJJ3D27FkA1TOJpkyZgtGjR+Ozzz5DixYt8Pjjj8Nkqh6F/frrr7F69WosXrwYH3zwAdLS0rBixQrzZy9fvhxHjhzBBx98gIULF2L16tXYvXu3uVzWPtseEjuHYllSj3o/rIgAnSL7jQAQmjYrJU5Onh5iPxbROFdnEryoFY2TU3PBhqdoHLkn5hMiIpILc0o10aVzDUbeBetIF0vEbngSjSNyZcWCe0+JxknFfFKtzCB4c65gHFFdRy8UyRrnDtQ+WKFGauy7r6HYYrwnT55EamoqfvrpJ4SGVlfAtGnTsGzZMlx77bXIysrCJ598Aj8/P0RHR+OXX37Bli1bMHXqVGzevBm9evXCxIkTAQBLly7FNddcg19//RUDBgzAhx9+iPvvvx9Dhw4FADz//PN46KGHMHPmTJhMJmzevBnvvvsuevbsiZ49eyIjIwMbN27E8OHD8d///tfqZ9tLYudQDIkOqV7PWqtVfD1rFa/khR7hvjhXaLvB0iOco/IA0MJHi3OXbW+608LH8WO9RpPYESQaR+6J+YSIiOTCnFJN7UvnuqsykY00JcQRuTL9ZcFVIgTjpGI+qdYuyBvpAuNG7YK4/BM1jknwRhPROHdRM1hRd/ndiAAdpg+N5vK7Fqit776GYjN3wsLCsG7dOnOSq1FcXIy0tDT06NGj1gbb8fHxSE1NBQCkpaUhISHB/Jyvry969uyJ1NRUGAwGHD58uNbzsbGxqKysxPHjx3H8+HFUVVUhLi6u1nunpaXBaDTa/Gx78tBqkNA2GCNjI5HQNljRg6NjC7HNzUXj5FRWJVYvonGurrBcrHEnGien1JwCWePIPTGfEBGRXJhTqjnD0rnu6EiO2F3HonFErqxccJl20TipmE+qHcgWa8uLxhHVZRK8GVg0zp0kdg7F9kcGYM3YPnjt7lisGdsH2x7uz4EdK9TUd19DsZk7gYGBGDx4sPnvRqMRH330Ea666irk5eUhPDy8VnxISAjOnz8PAFafLywsRHl5ea3nPT09ERwcjPPnz0Or1aJ58+bw9v7nroDQ0FCUl5cjPz/f5mdL0Zg9TGpeo8T+J1cKElwGK8jPy+FlzdBfFo5Tuh4b4shylQjOMi+pcvxxJ2WGmJLfpVp+l86iqfUl9XXMJ9LxWLaMv3XpWGfSsL6ka0qdNeY1rp5TROtEyka7PJ4dp6xK7Oq5rMrE70Wl+L04TveWAdh/xvaAQfeWATa/F+YTy0TqpahMbPCsqMzI30cjsM6AkkqxG5VLKg2sLws8PTTo1y4YISEBuHixCBwDs83RfV62KDa4U9eKFStw9OhRfPbZZ3j//fdrJSIA8Pb2RkVF9Z1hpaWlDT5fVlZm/rul500mk8XnAKCiosLqe0sVEhIg+TVyvFYOAc18hONCQ5UtqzVqLZsjy6XRQOjkrNE4vr6u79ka6/+bJRSnhu9S6d+ls1GqvphPbFPD70nN+FuXjnUmDetLOuYUeXKKaD3e2MIfrb7+A+cLyizejKMB0DLIBzfGRqnijkV34e2pERrg8fbUMNerFL8Xx7m+V2u8/2u2UJwjvhdXyyeAWE6pElwKq8po4u+jEVhngOgaNAawvmxhG0UatdSXKgZ3VqxYgQ8++ACvvPIKunTpAp1Oh/z8/FoxFRUV8PGpHnDQ6XT1Ek9FRQUCAwOh0+nMf6/7vK+vLwwGg8XnAMDHx8fmZ0vRmBFPjQaqGC3tESq2X02PUF/o9Q6e9m8SnDZtMjq+bIIcWS4/T6C4UizO0fXVKcgbgT6eKLSyiWWQjyc6BXkr+l2q5XfpLJpaXzWvbwzmEzFqPTcqjb916Vhn0rC+pGtKnTUlnwCumVOk1OPTQzri2e1HLT5n+vv5S38VS/p8apoOLXxwLLdUKI65Xp34vTjOpQKxFT8uFVyGXm/9XMp8YplITik3iCWdcoOJv49GYJ0BnoLTIDw1GtZXA9hGkUbJPi9LFB/ceeGFF/Dvf/8bK1aswE033QQAiIiIQGZmZq04vV5vnjoaEREBvV5f7/nu3bsjODgYOp0Oer0e0dHRAICqqirk5+cjLCwMJpMJly5dQlVVFTw9q//5eXl58PHxQWBgoM3PlsJkEpsxIfdr5dA3Khh+Xh5Wpzf6eXmgb1Sww8tZIXhxUGEwqfak5MhyabVaALYHxLRarcPrS6vRYGSvlthwsOE7qpJ6tYRWo1HFd6n079LZOLq+mE+kvR81jL91MQajqXozyaxC1Wwm6Sx4jEnHnCJPTpFSj0NtbLQ7tHMoj2MH89KKbZnrpcB1PYnh9+I4u4/mCscNbB9it3K4aj4B2EZRA9YZEOjjiQsCdzQH+niyvmxgG0UatdSX2NWhnaxevRqffPIJVq1ahVtvvdX8eExMDP73v/+Zp5sCQEpKCmJiYszPp6SkmJ8rLS3F0aNHERMTA61Wi969e9d6PjU1FZ6enujWrRu6d+8OT0/PWpvFpaSkoHfv3tBqtTY/273YOkKVOYJLK8Rm7ojGuToPwe9JNE5OBqMJXx+3ftH9ze95MAhO5Sb3xXxC5FjJGXokvbsfkzel48lPUjF5UzqS3t2P5Ay97RcTqRxzyj+40a66GAV7EETjiFzZ5QqxxZpE4xqD+YTI/oIF9wwXjSNyNooN7pw4cQJvvfUWHnnkEcTHxyMvL8/8p3///mjVqhXmzJmDjIwMrF27Funp6RgzZgwA4I477sChQ4ewdu1aZGRkYM6cOYiKisKAAQMAAOPHj8d7772HPXv2ID09HYsWLcLYsWPh6+sLX19fjBo1CosWLUJ6ejr27NmD9evX47777gMAm5/tLlKy8lFSaX1wpKTSiJSsfMcU6Aqi/fwcD6hmEpyiKhonp9Scglp3glpyoagcqTm2N8Ik98V8QuRYyRl6zNp+tN75O7e4ArO2H+UADzk15pT6PLQaJLQNxsjYSCS0DeYMPQUVlYt1QovGEbmyuMggWeOkYj4hcoz4NmK/YdE4Imej2LJs3333HQwGA95++228/fbbtZ77/fff8dZbb2HevHkYPXo02rVrhzfffBOtW7cGAERFReGNN97ASy+9hDfffBNxcXF48803ofm7c/rWW29FTk4OFixYgIqKCgwbNgwzZ840v/+cOXOwaNEi3H///fD398fUqVMxbNgwAICHh4fVz3YXh7LzheP6t2tu38LUpYHYpCG2OwEA5QKbrkqJk9P5wjLbQRLiyD0xnxA5jsFowsrkTKsxq/aewJDoEHYAk1NiTiE1yy8V2EhTQhyRK7szLhKvfX/KateB5u84e2A+IXKME7li+2uJxrkb81Lb2Vxq21lpTCbO2bYXvb5xG7+GhgY06rVyWv39SXxwoOF9UGrc3y8KT1zb0QEl+sfAVd9DZBzCUwP8Mv1a+xfob/1Wfi8ce2CG48o1YOX3AjvuVE/j2+/AcgHAsj0Z+CztnM24MTGtMOuGzg4okWVq+V06i6bWV83r6R8idanWc5Az4W/dtpSsfEzelG4zbs3YPohvE2z/AjkZHmPSNaXOmE/qa2pu5rGrrP4rvxe+x+1X5nqH4TWYej2z9X/Yd+Jig88PiQ7By6N62nwf5hPL2EaxD9aZNCPf/S/OFlpfEQYAWgd6Y9sjVzmgRM4jOUOPl7/LQN7lf24KCWvmhWeu78wleK1QW5+XYjN3SN2KK6pkjZOTQfCHIxrn6kSrgdVlGe9ikIb1ReTazheWyxpHROrH3K4evK4nEmcwmnDsQpHVmOO5xTAYTTynETmxSoPYftuice6iZqntuvIuV2LW9qNYltSDAzxOgoM7ZJFGcE0z0Tg5sVEjjVYjNtClxPVs6yCdrHFyS87QY2VyZq19JcL9vTEjsROTnAWsLyLXd/is2B5oh88W4NaeEXYuDRHZG3M7ETkrKfu7crYxkfPSeXgAsH3jeXUcAdWD30u++cNqzEvf/MGltp2EVukCkDq1ae4ra5ycRE8rPP1U8/MW+5mLxsnJaBQbghONkxM3DJeG9UXkHvKKxWbkiMYRkXoxtxORM8stErsWEY0jInXy9BDr/RONcweHsvJRWGZ9QKygrAqHsvIdUyBqEg7ukEVjYsQ20xONk5OX4FErGufqIgPFZr2Ixsnp8Dnr0+SlxslFdMNwgwKDTmrE+iJyH75eYne8icYRkToxtxORs7tUWmk7SEIcEalTgE5sUSrROHdwUHDQRjSOlMXub7JItKGmRIOuha/YaLtonKvLzi+TNU5OvoKzhUTj5CJlCj+xvojciZ+32KCNaBwRqRNzOxE5u+a+XrLGEZE6BejE+otE49yBRrC7VDSOlMUjmyx6/fuTssbJ6fxlsQEl0ThXVy6y4Y6EODl1DvWXNU4uehudGVLjXB3ri8h9eGjFLh1F44hInZjbicjZhQeIrUwhGkdE6nS2UOxaRDTOHfSNCpY1jpTFljdZlJVfKmscKcdolDdOTmH+YhfSonFyCfX3ljXO1bG+iNxHVJCPrHFEpE7M7UTk7GIjgxBu4xwVEaBDbGSQg0pERPaQb2PvGKlx7iC+TTCCfKwvUxfk44n4NsGOKRA1CQd3yKLIIMF9WgTjSDmi83GUmOcU2kyw40AwTi5sCEjD+iJyH9FhzWSNIyJ1Ym4nImfnodXgpm7hVmOGdQ2Dh5brDhE5s2Cd2HLQonHuwEOrwdxhXazGzB3WhedHJ8HBHbIoQnBqsmgcKUfNgztqLZuHVoMZiZ2sxkwfGs1E9zfWF5H7KCgVu+NNNI6I1Im5nYicncFowtfHc63GfPN7niL7CBORfPy8BPcEFYxzF4mdQ7EsqQfC6tzME+7vjWVJPZDYOVShkpFUHNwhi/53rljWOFKO6M0JStzEcPGy2JqnonFyqkl0de9ajQjQMdFZwPoicg9cqonIfSR2DsWEhCjUHb/RaoAJCVHM7USkaqk5Bci1sS/YhaJypOYUOKhERGQPeSWVssa5HZOpzl854O1srC+wR27rQlG5rHGknMhAH5y4VCYU52iXSsWSq2ic3BI7h2JIdAhScwpQrtVCZzQiNjKId6k2gPVF5Ppqlmqy1lnCpZqIXENyhh4bDmbXe9xoAjYczEav1oEc4CEi1TpbYLsNXBMX38bOhSEiu6k0iG0gLRrnLpIz9Ji1/Wi9x/MuV2LW9qO8SdeJcOYOWVRpMMgaR8opKhcbGBGNk1NzXy9Z4+zBQ6tBQttgjIyNRELbYA5U2MD6InJtXL+eyD0YjCasTM60GrNq7wkuZ0REqvWfTL2scUSkTs28xNodonHugNd5roWDO2SRv05sUpdoHCknv0xsAE40Tk6hzQSX9xGMIyIi++L69UTugcsZEZGzK6sUa9+KxhGROgX6ie0FLhrnDnid51o4uEMWXSc49U40jpQjOvNUiRmqBsG1PEXjiIjIvtgQIHIPehu/c6lxRESO1ra5n6xxRKRORWVVssa5g1zBLTZE40hZHNwhi8bERMoaR8oRXRlHiRV0RDv/lOwkrKgyYuPBbCzYdgQbD2ajoorrtBKR+2KHL5F7CPUXnF0tGEdE5GjTru0oaxwRqdPlMrF2h2icO1D7/tckDdfUIouOXigSjotvE2zfwlCTVAlOehGNk5NRcJxENE5ur+87iY0p2bhydaHX9p3EPfFRmDaEjQAicj9BvmKXjqJxRKROsZFBCPLxRIGVu1yDfDwRGxnkwFIREYnz9fZAVJAPsgvKGoyJCvKBr7eHA0tFRHIrqhDrzBKNcwfOsP81iePMHbKId+aSIwQKdv6Jxsnp9X0nseFg7YEdADCagA0Hs/H6vpMOLxMRkdKO54rd/CEaR0TqxS4QInJmFVVG5FgZ2AGAnIIyrsxA5OREF6FRYLEa1eL+166FgzsqYjCacPBMPral5uDgmXxFNyNu7ic4iisYR8oRPYqUONpC/MQShWicXCqqjNiYkm01ZmMKl2gjIvfzfcZFWeOISJ1ScwpQaGNt+oKyKu6vRUSqtem3HJttXNPfcUTkvCoFO7NE49yBmvsJSTqumaESyRl6rEzOrLVJcbi/N2YkdkJi51CHl8ckuIG9aByRJSGCdwGIxsnls7Sz9Wbs1GU0VceNj49yTKGIiFRAXyI4s1cwjojUibP4icjZpZ0VG3xOO1uAe9HGzqUhIlKPSyWCe+4IxpGyOHNHBZIz9Ji1/WitgR0AyC2uwKztR5GcoXd4mVKyxC6ERONIOWqeomoUHBwUjZNL1qVSWeOIiFyFj6fYuvSicUSkTi0EZ+eLxhEROZqPp1h3l2gcEZGrCPUXXJZNMI6UxSymMIPRhJXJmVZjVu094fAl2s4WiHVai8aRckS715TohjskODgoGicXzlwjIrJMaxJbjlI0jojUict1EJGz6xLuL2scEalTc53Yrcqice4gNjII4TYGbiICdIiNDHJQiagpOLijsNScgnozduq6UFTu8PWs84rKZY0j5VhfLV16nJwuFFnf4FJqnFx8vMWSvmgcEZGrOHlJLO+LxhGROnG5DiJydqHNdLLGEZE6BfiKzS4RjXMHHloNZiR2shozfWg0PLTs83IGHNxRWK7g4IhonFz+FFxuSjSOyJIWzQSX/BCMk0tGbomscUREroJ38xO5h+aCy62JxhEROVp4gNigjWgcEalTcblB1jh3kdg5FMuSetSbwRMRoMOypB6K7P9OjeOpdAHc3aVSwbviBOPkUmkQW05FNI7IktIKseNHNE4uPl6Ce0oIxhERuQoNxAZueI8XkXOrMIh1gIjGERE5WmxkEIJ8PFFQ1vAaFUE+nlx2iMjJiU4u4SSU+hI7h2JIdAhScwpQrtVCZzQiNjKIM3acDAd3FNbcV/CuOME4uXh7iP2QReOILNFoxI4f0Ti5hDUTm64rGkdE5Cr8vLS4XGl7wN3Pi5PDiZzZvw9mC8cN6sg7O4lInTiTmMj16QT7JUXj3I2HVoOEtsEIDQ2AXl8Ebi3tfNjyVphapwq3CvSRNY7IkjbNfWWNk0vv1oGyxhERuQqtRuxqXzSOiNTpnOCS0KJxRESOlppTgEIrs3YAoKCsyuH7GxORvDwFB21E44icjSoGdyoqKjBixAjs37/f/FhWVhYeeOABxMbG4pZbbsGPP/5Y6zU///wzRowYgZiYGNx3333Iysqq9fz777+PwYMHIy4uDnPnzkVp6T97w5SXl2Pu3LlISEjAoEGDsH79+lqvtfXZcoqNDKq3vmFdEQE6h08V9vMWm9QlGkdkyZiY1janxmo11XGO1FJw0FI0jhzHnfMJkSPw+oDciTvnFD8vwd+6YBwRkaPpiytkjWsKd84nRPZWViW2jL9oHJGzUXxwp7y8HNOnT0dGRob5MZPJhClTpiA0NBRbtmzByJEj8cQTT+Ds2bMAgLNnz2LKlCkYPXo0PvvsM7Ro0QKPP/44TH/PHfv666+xevVqLF68GB988AHS0tKwYsUK8/svX74cR44cwQcffICFCxdi9erV2L17t9Bny81Dq8GMxE5WY6YPjXb4eofdWwbIGkdkibenFoM7hliNGdwxBN6ejj1VqXXQlaxz93xC5Aj+3mLnY9E4IrVy95zSv32wrHFERI4W5Cs2+Cwa11junk+I7K1ScPs/0TgiZ6NoyzszMxNjx47FmTNnaj3+3//+F1lZWVi8eDGio6MxadIkxMbGYsuWLQCAzZs3o1evXpg4cSI6d+6MpUuXIicnB7/++isA4MMPP8T999+PoUOHok+fPnj++eexZcsWlJaWoqSkBJs3b8a8efPQs2dP3HjjjXj44YexceNGoc+2h8TOoViW1KNeZ3JEgA7LknogsbPj17Ee0K65rHFElhiMJhw4c8lqzIEzl2AwOnZ5H7UOulLDmE+IHKOoXKxVJBpHZI3BaMLBM/nYlpqDg2fyHXY9wJwC9G8rdo0vGkdE5GgZecWyxjUG8wmR/TXz9pA1jsjZKDq48+uvv2LAgAH49NNPaz2elpaGHj16wM/Pz/xYfHw8UlNTzc8nJCSYn/P19UXPnj2RmpoKg8GAw4cP13o+NjYWlZWVOH78OI4fP46qqirExcXVeu+0tDQYjUabn20viZ1D8cVD/fH0dR1x38B2ePq6jvh8Yj9FBnYAoG+bYAT6WL+DJcjHE33bBDumQOSSDpy5hBIbG3OXVBptDgDZgxoHXalhzCdEjlFmEFz2QDCOqCHJGXokvbsfkzel48lPUjF5UzqS3t2P5Ay93T+bOQWoMogNpInGERE5Wmq22F46onGNwXxCZH9tm/vZDpIQR+RsFF0kefz48RYfz8vLQ3h4eK3HQkJCcP78eZvPFxYWory8vNbznp6eCA4Oxvnz56HVatG8eXN4e//TYRsaGory8nLk5+fb/GwpNBJu6k/+Q4+XkzORe8V6rxsPZuOZxE5I7OL4TmRPDw3mD+uCZ7cfbTBm3rAuqt+QTMp34EgsV7Wvjl4QjhvYoYWdS1Pf9V1CcV2nEKTmFKBMo4WPyYjYyCDO2LGh5jhq7PHUmNcxnyj7fq6iqceuOyitEBu0Ka0wsh4t4DEmJvkPPWZZuAbNLa7ArO1HsTyph9D1cWPr2ZVzimidbDyYZTvo77jBnawvsUvK4HlGnfi9OE6u4F46ucUVNr8X5hPL2EZRHusMaB/ih5/+tH1DcPsQP9ZXA9hGkUaJPi9rVLkDZmlpaa1EBADe3t6oqKiw+XxZWZn575aeN5lMFp8Dqje5s/XZUoSEiO1Hs/vIOczafhR173vL+7sB+/a9fTG8VyvJn99UgeetT08ODPRBaKi699xRa/lYrmpVgme0Ko1G0Tq7KTxQsc92ZqLnQHtyt3wiSq3nILVQw7GrVibBm/RNJh5n1vAYa5jBaMIr+35t8HkNgFf2ncQdV7V3+M0WrpBTRI+947liyxQdzy3mb12l+L04jgao15ZvKI7fi+NEtmiG47mXheIc/b24Qj4B2EZRA9YZ8Gd+mXAc68s6tlGkUUt9qXJwR6fTIT8/v9ZjFRUV8PHxMT9fN/FUVFQgMDAQOp3O/Pe6z/v6+sJgMFh8DgB8fHxsfrYUFy8W2ewEMRhNWLD1iMWLwZrHFm77H+LCmzm0AVtTLmuUKJdUen2R0kWwiOWq1iO0Gb4RjFOyzjSa6pO2yG+aml5fNa+XgzvlEynUeg5SGn/rtmkEe7A0Gh5nlvAYs+3gmXycK2i4kW4CcK6gDN+mZiOhbbDV95IznwCukVNEj73yKrFZeuVVRv7WVYrfi+N4AKgSjOP34jjBOrFdCIJ1WpvfC/OJZWyjKI91BnhA7JrFA7xmaQjbKNKoqc8LUOngTkREBDIzM2s9ptfrzVNHIyIioNfr6z3fvXt3BAcHQ6fTQa/XIzo6GgBQVVWF/Px8hIWFwWQy4dKlS6iqqoKnZ/U/Py8vDz4+PggMDLT52VKYTLbvcP0tu8DmdOELReX4LbsA8Q7c30at5ZJKrSclR5ZLyp1kjq6vO+Mi8dr3p6yWT/N3nFLfpcFoQmpOAcqzCqEzclk2KUTOgfbmTvlE6vtRw9Rw7KqVTgvY2CrNHMc6bBiPsYbpBZfR0RdXOLwOXSGniB57zby1yC+z/WNv5q3lsaxS/F4cx9MDqDKIxfF7cZzerQKxJc32UmO9WwUyn7CN4rRYZ0DfyGB8f8L2smx9I4NZXzawjSKNWupL7FYGB4uJicH//vc/83RTAEhJSUFMTIz5+ZSUFPNzpaWlOHr0KGJiYqDVatG7d+9az6empsLT0xPdunVD9+7d4enpWWuzuJSUFPTu3RtardbmZ8tNSgPWkXKLymWNI+WIboukxPZJHloNfLysn4Z8vbSKDaYouZkzycOd8gmRIwjezC8cR1RXqL+37SAJcXJyp5wS5q+TNY7IlXloxbpVRONIHi0DxWaiiMbJyZ3yCZG93RkXCVs9RjU3DRO5IlVeXfTv3x+tWrXCnDlzkJGRgbVr1yI9PR1jxowBANxxxx04dOgQ1q5di4yMDMyZMwdRUVEYMGAAgOpN69577z3s2bMH6enpWLRoEcaOHQtfX1/4+vpi1KhRWLRoEdLT07Fnzx6sX78e9913n9Bny02tDdhLpZWyxpFyfL3EBkZE4+SUmlOAUhu3gJdUGpGaU+CgEv0jOaN6M+e6M9hqNnPmAI9zcKd8QuQIGsHBdtE4orpiI4MQbuO6NyJAh9jIIAeV6B/ulFN0nmLNRNE4Ilfm4+UhaxzJg/lEHfmEyN7UftMwkb2p8mrcw8MDb731FvLy8jB69Ghs374db775Jlq3bg0AiIqKwhtvvIEtW7ZgzJgxyM/Px5tvvgnN35uz33rrrZg0aRIWLFiAiRMnok+fPpg5c6b5/efMmYOePXvi/vvvx/PPP4+pU6di2LBhQp8tN7VecDT39ZI1jpRjMIrNERSNk5NaZ64ZjCasTM60GrNq7wlF6oykcad8QuQIHhqxRpFoHFFdHloNZiR2shozfWi0Ig10d8opvl5iq3eLxhG5sjvjWskaR/JgPlFHPiGyNzXfNEzkCBqTSQ2rw7kmvV5sY6WaGQINWZbUA4mdQ2UsmW0pWfmYvCndZtyasX0cvudOv5XfC8cemHGtHUtSm1rLNXDV96gSOA49NcAv0x1XLkC9x5lay+UsNBogNDRA+BzY0OvpHyJ1qdZzkDNp6rHrDm5f+zOyi2xvGx0V4IkvHr3aASVyLjzGxCVn6LEyObPWDNqIAB2mD40Wvi5mPqlP9Nh74/sT+PBAjs24+/pFYuq10TKUjEQw16tTaYUB177xk82476deA19vzt5xJLn6WphPLGMbxT6uffV7lArs4+XrAXz/FOvs62O5mP/lcZtxL97SDTd1l763lDtgG0UatfV58VYrFUjsHIplST2a3ICVU48IsYNMNI4UJHqiUeAE3rtVILQawNoEGK2mOs6R1DqjiIhIaYXlAi1NCXFEDUnsHIoh0SFIzSlAuVYLndGI2MggLqnhIIE6sWaiaByRKzt6oUg4jjeGOY7oagxDokOYW0hVgv28UFpkewuEYD+upAOod7sLIkfh1bhKqK0B+8Xhc8Jx4+Oj7Fwaago/nRaF5bZ3tvbTOX6VxsPnCq0O7ADVAz+HzxU6tCHEiwMiIstKKsXuBBCNI7LGQ6tBQttg3kmogAz9ZVnjiFzZ+cIy20ES4kgeqTkF9fZPretCUTlScwo46EaqYrTdfSMpztXVbHdh7feu1P5aRI6gyj133FVNA3ZkbCQS2gYrevfImb9KZY0j5bQJ9pU1Tk5qnSFTM6PIGiVmFBERERE5wvnCclnjiFzZ4bOFssaRPHKLxM5PonFEjqLixVdUyUOrwU3drC+3NqxrGGfokcvi4A5ZdKFIbNBGNI6U06a5n6xxcmouOI1YNE4uUmYUERG5kxZ+YnsFiMYRkTp5CXaAiMYRuTL9ZcEb1gTjSB6XSm0vayUljshR2rbwkTXO1RmMJnx9PNdqzDe/58Fgq5OHyElxcIcsyrpUImscKefWnhGyxslJtDvA0d0Gap1RRESkNKNJ7IwsGkdEasX7holE+XmL3dAgGkfyaO4reCOhYByRowxo10LWOFcnZQlGIlfEwR2yqKBMbCNk0ThSTt+oYFnj5PRXidhdUqJxcuGeO0RElnl5iF06isYRkTqVV4kN2ojGEbmyW3sI3kwnGEfyCA/QyRpH5CgRAWIzckTjXB1vziV3x5Y3WeTjJXZoiMaRckSXDlNiiTG1DqLUbMhnDTfkIyJ3FCZ4PhaNIyJ1qhBcukQ0jsiVJbRtDl8b7WI/Ly0S2jZ3UIkIYJuOnBcHJqVRa78SkaOwZ54sah3kK2ucnLwFV3oRjZMLlxiTLjYyCIE+nlZjgnw8HX7B7aHVYEZiJ6sx04dGc0M+InI7Sb1byhpHROoUIdgBIhpH5Mo8tBosurmb1ZiFN3dj28HB2KYjZ8WBSWlYX+TuOLhDFoU1E7wzVzBOTt0imskaJ5cQwc2jRePkova7GNR6KZ3YORTLknrUu0iICNBhWVIPJHYOVahkRETKiQr2kzWOiNRJtAOEHSVE1RI7h2JCQpTF5yYkRLHtoBC26cgZeWg1uKlbuNWYYV3DODD5Nw7kkruzfss8uS01z9yxtVGa1Di53B7TCu/+ki0U50g9IgJkjZNTak4BCsqqrMYUlFUhNacA8W2CHVOoKyR2DsWQ6BCk5hSgXKuFzmhEbGQQLwpIlTQQ29aaRy81Re9WgTaPNc3fcUTkvNq1EBugFY0jeXgAENnx1LG3khEAJGfoseGg5bbghoPZ6NU6kAMJCmGbTllso0hnMJqw7ch5qzHbj5zHlMEdeBz/rWYgd2VyZq2+wIgAHaYPjeb5l1waB3fIorioQPzrV7E4Rysstz4YIDVOLlUGsaQqGieXLw6fE44bH2/5bjN7UfOScTU8tBoktA1GaGgA9PoimLi0PKmU6KHJQ5iaIi2nwOYxZPo7rl877i1A5Kz+nWL7hqWauGs7scOE3JvBaMLK5EyrMav2nsCQ6BB2xCqEbTrlsI0i3aGsfBQK3AR7KCuf19tX4EAuuSsuy0YWZeRdljVOViq9OtAI5gvROLlk55fJGicntS8ZR0REtR3Mypc1jojU6fSlUlnjSB7eglNyRONIHqk5BTZXjbhQVI7UnAIHlYiInBmvtxuvZiB3ZGwkEtoGc2CH3AIHd8ii9LNFssbJKUAnNuFMNE4uCYLLhonGySUq2EfWODlx4zsi+XgJXreKxhFZotYbGYhIXp6CnSGicSSPSMHrddE4koczrEZApBRPwTQhGucOeL1NRFJwcIcs8hO83Us0Tk4egglMNE4ufdsEI9DH+oBSkI8n+jp4cGdMTGvYandrNdVxjsaN74jkoxNsEYnGEVnSNypY1jgiUicOIqhTsK/YbHbROJIHVyMgahjbKNLxepuIpODgDlk0vFu4rHFy8vAUG1ASjZOLh1aDecO6WI2ZO6yLwwcqvD21uMfGXjr3xEfB21OZ00HNxnd1Z/BEBOiwLKkHN74jEqQT/A2LxhFZEt8mGEECNzLEO/hGBiKSV8+WYvtqisaRPMqrjLLGkTy4GgFRw3y9xPplROPcAa+3iUgK9vCQRVrBI0M0Tk4tA8TueBKNk1Ni51BMSIhC3eEbDYAJCVGKDVRMG9IRExKi6s3g0WqqyzVtSEdFylUjsXMotj8yAGvG9sGLt3TDmrF9sO3h/hzYIZKghZ+XrHFElnhoNZirwhsZiEheAwQ3aBaNI3nwDnh14moERA1r7iu2XL5onDvg9TYRScGzJ1kkutljak4Brmrfws6lqW1AuxY4kFUoFOdoyRl6bDiYXe9xE4ANB7PRq3WgogM8k69pj8/SzuJiuQEhOg+MiWmt2Iydujy0Gt55QtQEQb7eAMoE44gar2bG5crkzFobSEf46zA9MZoD80QuoGa54cKyqgZjlFhu2N1pBDdYEI0j+TSYGwN0mD6UuZHcF9sojcPrbSISxcEdsshkkjdOTmpd09hgNGFlcqbVmFV7T2BIdIhid1h4e2pxT0IUQkMDoNcXKfL9EZF9cMkDcqTEzqEYEh2C1JwClGu10BmNiI0M4h2ERC6iZrnhWduPNhjDu4Ydz0dw2WnROJIXcyNRfWyjNB7PKUQkQh237JPq9I0SWw9YNE5Ol0orZY2TS2pOQa07Kiy5UFQuPCuKiEgKE8TW1xeNI7LFQ6tBQttgjIyNRELbYDY0iVxMzV3DYc1qL+cZ7u/NfREVwlyvfsyNRLXxvNU0PKcQkS2cuUMWqXnKf2Fpw8tDNCZOLnobAztS44iIpCgoE2sQicYRERHxrmF1Ya4nImfD8xYRkX1xcIcsulQiODtGME5OWsH5ZqJxclHrcnFE5B48BPvZROOIiIiAf+4a5rK+ymOuJyJnw/MWEZF9cVk2skjNAxV9o4JljZNLbGQQwm3UR0SADrGRjl/Kjohc37WdQmSNIyIiInVhriciZ8PzFhGRfXFwhyxS80BFfJtgBPlYn3QW5OOJ+DbBjinQ3zy0GsxI7GQ1ZvrQaC5jQUR2cVdcFGydXTR/xxEREZHzYa4nImfD81bTGIwmHDyTj22pOTh4Jh8GI6fPElFtHNwhi9Q8UOGh1WDusC5WY+YO66JI2Wo2nq07MBYRoOPGs0RkV96eWtybYL1RdG9CFLw9mfqJiIicEXM9ETkbnrcaLzlDj6R392PypnQ8+UkqJm9KR9K7+5GcoVe6aESkItxzhxpUM1CxMjkTucUV5scjAnSYPjSaAxUNuHLjWX1xBUL9vbnxLBE5RK/WgU16noiIiNSNuZ6InM20IR0BABtTsnHlxBOtBrgnPsr8PP0jOUOPWduP1ns8t7gCs7Yf5c3DRGTGwR2ySo0DFQajCSuTM63GrNp7AkOiQxQrp4dW4/Bl4YjIvTnDuZGIiIgaj7meiJzVtCEdMfma9vgs7SwulhsQovPAmJjWnLFjAc/1RCQFz6INKC8vx9y5c5GQkIBBgwZh/fr1ShdJMTUDFTd1D0d8m2DFk0dqTkGtmUSWXCgqR2pOgYNKRETUMEflE54biYhcH9so7o25nojkokQ+8fbU4p6EKCwe2Qv3cCm2BvFcT0RScOZOA5YvX44jR47ggw8+wNmzZzFr1iy0bt0aw4cPV7pobk9vI8lJjSMisidH5ROeG4mIXB/bKO6NuZ6I5MJ8ol481xORFBzcsaCkpASbN2/Gu+++i549e6Jnz57IyMjAxo0bmehUINTfW9Y4IiJ7cWQ+4bmRiMi1sY1CzPVEJAfmE3XjuZ6IpOAcSAuOHz+OqqoqxMXFmR+Lj49HWloajEajgiUjAIiNDEK4jSQWEaBDbGSQg0pERGSZI/MJz41ERK6NbRRiriciOTCfqBvP9UQkBQd3LMjLy0Pz5s3h7f3PyTQ0NBTl5eXIz89XrmAEoHoPoBmJnazGTB8arfjeQEREjswnPDcSEbk2tlGIuZ6I5MB8om481xORFFyWzYLS0tJaSQ6A+e8VFeJrWmoacZ6teU1jXutOru8SiuVJPfBycmatjeYiAnSYMTQaiV1CFSyduvEYk451Jk1T68uV6tnR+YTnxqbhb1061pk0rC/pmlJnrlbPcuSUpuZmV6tTZ8Rcr378vagT88k/2OelfjzXNx6PMelYZ9Korc+LgzsW6HS6egmt5u8+Pj7C7xMSEtDoMjTlte5ibGgA7riqPX499Rdyi8oQHuCD/h1a8O4FQTzGpGOdScP6Uiaf8NzYdDx2pWOdScP6ko51Jk9OaWo98ntQB+Z658Dfizrxe2Gfl7Pgub5peIxJxzqTRi31xcEdCyIiInDp0iVUVVXB07O6ivLy8uDj44PAwEDh97l4sQgmk7TP1miqD47GvNZddQn2xsDoEFy8WIRLfxUrXRzV4zEmHetMmqbWV83rXYGS+YTnRun4W5eOdSYN60u6ptSZK+UTQJ6c0tTczGNXXZjr1Ym/F3ViPvkH+7ycC8/10vAYk451Jo3a+rw4uGNB9+7d4enpidTUVCQkJAAAUlJS0Lt3b2i14tsUmUxo9I+iKa91V6wzaVhf0rHOpGF9MZ84K9aZdKwzaVhf0rHO5MkpTa1Hfg/qxO9Fnfi9qBO/F7ZRnBXrTBrWl3SsM2nUUl/iZ2034uvri1GjRmHRokVIT0/Hnj17sH79etx3331KF42IiJwI8wkREcmFOYWIiOTAfEJE5Do4c6cBc+bMwaJFi3D//ffD398fU6dOxbBhw5QuFhERORnmEyIikgtzChERyYH5hIjINWhMJjVMIHJNen3j1h8NDQ1o1GvdFetMGtaXdKwzaZpaXzWvp38wnzgG60w61pk0rC/pmlJnzCf1NTU389hVF34v6sTvRZ2YT+THNopjsM6kYX1JxzqTRm19Xpy5Y0caTeNf05jXuivWmTSsL+lYZ9I0tb5Yz/UxnzgG60w61pk0rC/pmlJnrOf6mpqbWafqwu9Fnfi9qBPzifzYRnEM1pk0rC/pWGfSqK3PizN3iIiIiIiIiIiIiIiInIhW6QIQERERERERERERERGROA7uEBEREREREREREREROREO7hARERERERERERERETkRDu4QERERERERERERERE5EQ7uEBEREREREREREREROREO7hARERERERERERERETkRDu4QERERERERERERERE5EQ7uEBEREREREREREREROREO7hARERERERERERERETkRDu6oSHl5OebOnYuEhAQMGjQI69evV7pIqnbhwgVMmzYN/fv3x+DBg7F06VKUl5crXSyn8eijj2L27NlKF0P1Kioq8Pzzz6Nfv364+uqrsWrVKphMJqWLpVrnzp3DpEmT0LdvXyQmJuL9999XukhuoaKiAiNGjMD+/fsbjDl69CjuvPNOxMTE4I477sCRI0ccWEL1Eamzxx57DF27dq31Z+/evQ4spfKk5FoeY9Wk1BmPsWqnT5/GQw89hLi4OFx33XVYt25dg7E8zhzr888/R9euXbF582ali+K2EhMTzeeHbt26IS4uDnfffTd++OEHpYtGAEpKSvDqq69i+PDh6NOnDwYMGIBp06YhIyND6aIReA5TG/Z5NY5Iu4WqsZ9QOinX4VSbWvpVObijIsuXL8eRI0fwwQcfYOHChVi9ejV2796tdLFUyWQyYdq0aSgtLcXGjRvxyiuvYO/evXj11VeVLppT2LVrF/bt26d0MZzCiy++iJ9//hnvvfceVq5ciU2bNuHTTz9Vuliq9dRTT8HPzw+ff/455s6di1dffRXffvut0sVyaeXl5Zg+fbrVToSSkhI8+uijSEhIwOeff464uDhMmjQJJSUlDiypeojUGQCcOHECK1aswI8//mj+c8011ziolMqTkmt5jFWTen3i7scYABiNRjz66KNo3rw5vvjiCzz//PN4++23sWPHjnqxPM4cb9euXWjbti22bdumdFHc2ty5c/Hjjz9i3759+PTTT9G3b19MmjQJP//8s9JFc2uXL1/GuHHjsGvXLsycORNfffUV3nvvPTRr1gx33303srKylC6i2+M5TF3Y5yWdaLuF2E/YGFKuw6k2NfWrcnBHJUpKSrB582bMmzcPPXv2xI033oiHH34YGzduVLpoqnTy5EmkpqZi6dKl6Ny5MxISEjBt2jTs3LlT6aKpXn5+PpYvX47evXsrXRTVy8/Px5YtW/DCCy+gT58+GDhwICZOnIi0tDSli6ZKBQUFSE1NxWOPPYb27dvjhhtuwODBg/HLL78oXTSXlZmZibFjx+LMmTNW47788kvodDo8++yziI6Oxrx589CsWTO3bEyJ1llFRQWys7PRu3dvhIWFmf94e3s7qKTKk5JreYxVk1JnPMaq6fV6dO/eHYsWLUL79u0xZMgQDBw4ECkpKfVieZw51sWLF/HLL79gypQpOHjwIDuqFRQQEICwsDBERESgS5cuePbZZ3Hrrbdi6dKlShfNrb355pu4ePEitmzZguuvvx6RkZHo1asXli5dit69e3MGu8J4DlMX9nlJJ9puoWrsJ5ROynU4/UNt/aoc3FGJ48ePo6qqCnFxcebH4uPjkZaWBqPRqGDJ1CksLAzr1q1DaGhorceLi4sVKpHzWLZsGUaOHIlOnTopXRTVS0lJgb+/P/r3729+7NFHH2VDugE+Pj7w9fXF559/jsrKSpw8eRKHDh1C9+7dlS6ay/r1118xYMAAm7PJ0tLSEB8fD41GAwDQaDTo27cvUlNTHVBKdRGts5MnT0Kj0aBNmzYOKpn6SMm1PMaqSakzHmPVwsPD8eqrr8Lf3x8mkwkpKSk4cOBArdxbg8eZY+3evRsBAQFISkpCeHh4rTvfExMTsWLFCgwaNAijRo3ikrUKuOuuu/DHH3/g9OnT6Nq1a63lej7//HMkJiYqWDrXZzQa8cUXX+DBBx9EYGBgveeXL1+OmTNnWvwuJkyYgDfeeMNRRXVb1s5hZWVlmDdvHuLj4zF48GBs3rwZPXr0QHZ2toIldm3s85JOtN1C1dhPKJ2U63D6h9r6VT2VLgBVy8vLQ/PmzWvdrRkaGory8nLk5+ejRYsWCpZOfQIDAzF48GDz341GIz766CNcddVVCpZK/X755RccPHgQO3bswKJFi5QujuplZWUhMjISW7duxZo1a1BZWYnRo0fjscceg1bLsfG6dDodFixYgBdeeAEffvghDAYDRo8ejTvvvFPporms8ePHC8Xl5eXVu/AICQlxy+n9onV28uRJ+Pv749lnn8Wvv/6Kli1bYurUqRgyZIidS6geUnItj7FqUuqMx1h9iYmJOHv2LIYOHYqbbrqp3vM8zhxr165duO6666DVapGYmIitW7diypQp5sG1HTt24L333oPJZDI/Ro4THR0NoPrObnK8M2fO4K+//kJCQoLF58PDwx1cIqrL2jnsxRdfxG+//Yb33nsPVVVVmDdvHgwGg9JFdmns85JOtN1C1dhP2DS2rsOpmhr7Vdk7qRKlpaX1luGo+XtFRYUSRXIqK1aswNGjR/H0008rXRTVKi8vx8KFC7FgwQL4+PgoXRynUFJSgtOnT+OTTz7B0qVLMWvWLGzYsIFLLFhx4sQJDB06FJ9++imWLl2K3bt3Y/v27UoXy+01lGOYXxp28uRJlJWVYdCgQVi3bh2GDBmCxx57DIcPH1a6aIqxlmt5jFlmrc54jNX3+uuvY82aNTh27JjFWbI8zhzn3LlzOHToEG644QYAwLBhw5CVlVVrmY6kpCR07doV3bp1U6qYbi0gIABA9b4v5HiXLl0CAAQFBZkf+/nnnxEXF2f+c+uttypVPLdn7Rx2+fJlbN26Fc899xxiY2ORkJCA+fPnK1xi18c+L3I09hNKY+s6nNTbr8qZOyqh0+nqJbSav6vpgFGjFStW4IMPPsArr7yCLl26KF0c1Vq9ejV69epV604Gss7T0xPFxcVYuXIlIiMjAQBnz57Fv//9b0ycOFHh0qnPL7/8gs8++wz79u2Dj48PevfujQsXLuDtt99GUlKS0sVzaw3lGOaXhj3++OOYMGGCudOmW7du+N///odNmzapZm1dR7KVa3mM1WerzniM1Vfz7y4vL8czzzyDZ599tlZHEI8zx9m1axd0Oh0GDRoEAOjfvz+CgoLwxRdfmGcq1FwbkTJqlpnx9/dXuCTuqWYptsLCQvNjcXFx2Lp1KwDgm2++wb///W8likawfg7T6XSorKyslWuvXCqM7IN9XuRI7CeUztZ1OKm3X5WDOyoRERGBS5cuoaqqCp6e1V9LXl4efHx8LK7hS9VeeOEF/Pvf/8aKFSs4bdCGXbt2Qa/Xmy9cay6kvv76a/z2229KFk21wsLCoNPpanVedOjQAefOnVOwVOp15MgRtGvXrtbFeY8ePbBmzRoFS0VAdY7R6/W1HtPr9VwyxAqtVlvrblwA6Nixo1sufyOSa3mM1SZSZzzGqun1eqSmpprvrgaATp06obKyEsXFxbWWaeFx5ji7du1CWVkZ4uPjzY8ZDAbs3r0bzz33HIDqjjpSzu+//w4A6Ny5c73nuLyU/bVr1w7BwcH47bff0KdPHwCAr68v2rVrB6B6yUgAFpcsrKqqclxB3ZS1c9iYMWPqxXPfMPtjnxc5CvsJxUm5Dif19qtycEclunfvDk9PT6SmpprvhktJSUHv3r25t0cDVq9ejU8++QSrVq3C8OHDlS6O6m3YsKFWQ+Lll18GADzzzDNKFUn1YmJiUF5ejlOnTqFDhw4AqpfR4Z2qloWHh+P06dOoqKgw3+Fx8uRJREVFKVwyiomJwbvvvmveF8FkMuHQoUOYPHmy0kVTrdmzZ0Oj0dSakn78+HG3u/NLNNfyGPuHaJ3xGKuWnZ2NJ554Avv27UNERASA6psFWrRoUa9ByePMMU6dOoWjR49i/vz5GDBggPnxzMxMPP300/j2228VLB3V2LJlC3r27Ik2bdrAy8ur1vJsWVlZCpbMPXh6euKOO+7ABx98gDvuuKPeDKoLFy4AQL3vxmQyITs726FldTe2zmGnT5+Gl5cXjhw5Yt6L48iRI0oV122wz4scgf2E0ki5Dif19qvyDKoSvr6+GDVqFBYtWoT09HTs2bMH69evx3333ad00VTpxIkTeOutt/DII48gPj4eeXl55j9kWWRkJNq1a2f+06xZMzRr1sx8dxnV17FjR1x33XWYM2cOjh8/jh9++AFr167FuHHjlC6aKiUmJsLLywvz58/HqVOnkJycjDVr1mDChAlKF80t5eXloaysDAAwfPhwFBYWYsmSJcjMzMSSJUtQWlqKm2++WeFSqsuVdZaYmIgdO3Zg69atOH36NFavXo2UlBTce++9CpfScWzlWh5j9UmpMx5j1Xr37o2ePXti7ty5yMzMxL59+7BixQrzgA2PM8fbtWsXgoODcdddd6FLly7mP7fccgs6depkXnaKHKeoqAh5eXnIzc3F77//jiVLluDLL7/E7NmzAVT/jj766CP8+eef+O677/D5558rXGL3MHXqVISFheHuu+/G7t27kZWVhfT0dDz33HN4/fXXER8fj169eiE/Px8bNmxAVlYWli5dioKCAqWL7tJsncN27NiB0aNHY8mSJUhLS0NqaiqWLFkCwPJMK5IH+7zI3thPKJ2t63CqTa39qhzcUZE5c+agZ8+euP/++/H8889j6tSpGDZsmNLFUqXvvvsOBoMBb7/9NgYNGlTrD5GcXn75ZbRt2xbjxo3DrFmzcM8993CwogEBAQF4//33kZeXhzFjxmDp0qV47LHHcNdddyldNLc0aNAgfPnllwCq1+N/5513kJKSgtGjRyMtLQ1r166Fn5+fwqVUlyvrbNiwYVi4cCHefvttjBgxAsnJyVi3bp1bzUSzlWt5jNUnpc54jFXz8PDAW2+9BV9fX9x1112YN28eJkyYYO7s4XHmeLt27cJtt91mcZ31cePG4eeffzbPSiDHeOmllzBo0CBce+21ePDBB3Hq1Cm8//776N+/PwDgueeeQ35+PkaMGIF169Zh2rRpCpfYPfj6+mLDhg0YOXIk3nrrLYwYMQIPPfQQzp49izfeeAMrVqxA+/btMWvWLLz99tsYNWoUTCYTlwmyM5Fz2KRJk9C1a1c88MADmDp1KkaMGAGgeqYV2Q/7vMie2E8ona3rcHIOGhMXFyUiIiIiIiIiIjewZ88eDBw4EM2aNQMApKenY/z48fjtt984wENERE6Fe+4QEREREREREZFbWL16Nfbu3YtHH30Uly9fxooVK8xLTBMRETkTztwhIiIiIiIiIiK3kJmZiRdeeAHp6enw9vZGYmIi5s6di4CAAKWLRkREJAkHd4iIiIiIiIiIiIiIiJyIVukCEBERERERERERERERkTgO7hARERERERERERERETkRDu4QERERERERERERERE5EQ7uEBEREREREREREREROREO7hARERERERERERERETkRDu4Q2UFlZSXeeOMNXH/99ejVqxeuu+46LF26FMXFxTZf27VrV+zfv9/ic/v370fXrl2Fy/HGG28gPj4eCQkJVj/7jTfewIQJE4Tfl4iI1M1SLvn+++/Rs2dPvPHGG3b97NmzZ2P27Nl2/QwiIiIiInJujm6zTJgwwe5tISJH4+AOkR28/PLL+Oabb/Diiy9i9+7dWLp0KX766Sc888wzDitDQUEBVq9ejVmzZmHbtm3w9/dvMHbixIlMcERELiwtLQ1PPvkkxo8fj6lTpypdHCIiagJXH8A/duwYpk6dioEDB6Jv374YN24c9uzZI+tnXFmHiYmJ+PzzzwEAxcXF2Lp1q2yf89VXX+HixYuyvR8RkSuzd5vljTfewMSJE2V/XyIlcXCHyA6++OILPPnkkxg4cCCioqIwcOBALFq0CHv37kVubq5DylAzU2fgwIGIjIy0GtusWTMEBwc7oFRERORoJ0+exKOPPorhw4dj7ty5SheHiIhk5koD+D///DPGjRuHli1b4l//+he2bNmCG2+8ETNmzMCaNWvs8pmfffYZbrnlFgDA+++/jy1btsjyvjk5OXjqqadQWloqy/sREbkyR7RZgoOD0axZM7u8N5FSOLhDZAcajQb//e9/YTQazY/FxcVh165daN68OUpKSrBgwQIMGDAAAwYMwHPPPYfy8nJz7MGDB3Hbbbehd+/euPfee5GTk2Pxc1JSUjBu3DjExMQgNjYWjzzyCHJzc5GdnY3ExEQAwA033IDZs2djwoQJ6Nq1a70/OTk5tZZl+/zzzzFhwgS8/fbb6NevH6655hps3boVu3fvxtChQ5GQkIAVK1aYy5CYmIjPPvsMd9xxB/r06YOJEyciJycHU6dORUxMDEaOHImMjIxa/7bRo0ejT58+uO222/D111+bn6u5EzApKQkDBw7En3/+Kcv3QUTkri5cuICHH34YAwYMwIsvvgiNRmN+ru6d359//rk5dwDAH3/8gQkTJqBPnz646aabsHHjxlrvvW3bNgwfPhwxMTG4++67cfToUfNzxcXFePrppxETE4PrrrsOO3bsMD9XUVGBF1980ZwDn3nmGeTn5wMAsrOz0bVrV3zzzTe44YYb0Lt3b0yaNMn8PBER1eZKA/gVFRWYO3cuHnjgAcybNw/dunVDhw4dMHHiRKxYsQKvv/46jh8/LvvntmjRAj4+PgAAk8kk2/vK+V5ERK7MWpslMzMTDz30EOLi4tC7d2+MHz8eJ06cAFC9dUFNn9Q111yDfv364d1338WBAwcwfPhwxMXF4dlnnzX3zV25LNvs2bOxdOlSPPXUU4iJicGQIUNqzdy01mYhUhMO7hDZwX333YcNGzYgMTERCxcuxNdff42ysjJ06tQJXl5emD9/PlJSUvDWW29h/fr1SElJwauvvmp+/ebNmzF//nx89tlnKCgowMsvv1zvM4qKijBp0iRcc8012LlzJ9577z2cOXMGa9euRatWrbB582bze82bNw9vvPEGfvzxR/z444/4/vvv0atXL9x0000WZ/X89ttvyMrKwmeffYZbb70VixYtwocffoi3334bs2fPxrp162p14r366quYMWMGPv74Yxw9ehS33347rr76anz22Wfw9fXFqlWrAAB5eXmYNGkSRo8ejR07duDhhx/G7NmzcfDgQfN7bdu2DU899RTeeecdtG/fXqZvhIjI/RQVFeHhhx9Gfn4+/u///g8eHh7Cry0rK8MjjzyC+Ph4bN++HbNmzcJbb71lbvD88MMPmDdvHu6//35s374dvXr1wqRJk1BRUQEA+Pbbb9GzZ0/s3LkTN998M+bOnYuioiIAwKpVq3DkyBG8++67+PDDD1FcXIwnn3yy1uevWbMGq1atwkcffYTDhw/jX//6lzyVQkTkQlxtAP/777+HXq/Hww8/XO/fOmzYMERHR5tn1VjaM7Tu8mpz5szBwIED0atXLwwfPrzBpd1qXvf5559j9erV+PXXX837nF64cAHTpk1Dv3790KtXL9x+++1ISUkxv/bcuXOYPHkyYmJikJiYiNWrV8NgMAAArr/+evN/a8pFRES1WWuzGI1GTJ48GZGRkdi2bRs++eQTGAyGWjcc5+bmYs+ePdiwYQMmT56MVatW4aWXXsL//d//YdWqVfjyyy/x3XffWfzsjRs3mtssw4YNw8KFCyW1WYjUgIM7RHYwZcoUrFixAi1btsSmTZswbdo0DB48GFu2bEFBQQF2796NBQsWID4+Hj179sTixYvRunVr8+sfe+wxDBgwAF27dsWYMWMs3qFWVlaGxx9/HFOmTEGbNm0QHx+PYcOGISMjAx4eHmjRogWA6jvRAgICEBwcjLCwMISFhWHDhg0oKirCSy+9ZLH8JpMJ8+fPR7t27XDXXXehtLQUU6dORbdu3TBmzBiEhITg5MmT5vjRo0fj6quvRq9evXDVVVehc+fOGDduHDp37oykpCRz7MaNG3H11Vfj3nvvRbt27TBy5Ejcdddd+OCDD8zv1bt3byQmJqJPnz6yfBdERO5q4cKF8Pb2htFoxPr16yW9dseOHQgJCcFTTz2F9u3bIzExEZMnT8aHH34IAPj0008xYsQIjBs3Du3atcOzzz6LESNGoKCgAED1bNWHH34Ybdq0weOPP46KigqcPHkSpaWl+Oijj/D888+jT58+6Nq1K5YvX45ff/0Vv//+u/nzp02bhj59+iAmJga33XYbDh8+LF/FEBG5AFccwE9PT0eHDh0a3Cs0Pj5eOB8sWbIEp06dwvr167Fz504kJCRg3rx55n+DJbfccgsmTpyIuLg4/PjjjwCAZ555BgaDAZ988gm2bt2KiIgILFq0CEB1m+mJJ55ASEgIvvjiCyxduhQ7duwwLx935c12Ncu+ERFRbdbaLGVlZbj77rsxe/ZstG3bFj179sTtt9+OzMxMc0xlZSVmzZqFjh074p577oHRaMQ999yD2NhYDB06FN27d6/Vf3Wlrl274pFHHkGbNm3w5JNPoqysDBkZGcJtFiI18FS6AESuKikpCUlJSbh06RJ+/PFHfPTRR5g3bx46deoEg8GAnj17mmMTEhKQkJBg/nvbtm3N/x8QEFBrybYaYWFhGDVqFN5//30cO3YMmZmZ+P3339G3b1+r5aq5o+GTTz5psOEUEhICPz8/AIBOpwMAREVFmZ/38fGp1TBq06ZNreeunA3k4+ODyspKANXLRuzduxdxcXHm5ysrK9GhQwfz323tD0RERGJatGiB9evXY8uWLVi1ahVuuOEGdOvWTei1J0+exPHjx2udrw0Gg7nz8NSpU7j77rvNz3l7e2PWrFnmv1+ZFwICAgAA5eXlyMrKQmVlZa3XAtV35f3555/m3NiuXTvzc/7+/uY8QkRE1RYuXIiWLVuaO8OeeOIJ4ddeOYAPAO3bt0dOTg4+/PBDjBo1qtYAPgA8++yz8PLyqjeADwCPP/441q9fj5MnT6JLly746KOPsGXLFvPMl+XLl2PAgAH4/fffzfsc1AzgA6g1gH/p0iWreyEEBQXh0qVLQv/Gfv364cEHH0SXLl0AABMnTsTmzZtx8eJFtGrVyuJrfHx84OfnBy8vL4SFhcFkMuGGG27ATTfdhJYtWwIA7rnnHjz66KMAgP/+9784e/YsNm/eDK1Wi44dO2LWrFmYM2cOpkyZUutmu5pl34iIqDZrbRY/Pz+MGzcOW7duxZEjR3Dy5EkcPXoUoaGhtd6jpu1Rc66t2yfV0MD+lavF1PSPVVVV2Wyz1OQ4IjXg4A6RzI4fP46tW7di9uzZAIDmzZvjtttuw0033YRhw4bhwIEDNt9Dq7U9qe7ChQu444470LNnT1x99dUYO3Ys/vOf/yAtLa3B15w+fRqzZ8/GvHnz0L179wbjPD3rnxquXOahrrp3CjZU/qqqKtx2222YPHlyg59XM5hERERNM2fOHAQFBeH+++/Hzp07MWfOHGzevNniOR6AeRkZoPp8PXDgQCxYsMBibEPvUcPSHeQmk8n8GR9//LH5JoIaISEh5qV5vLy8rL4/EZG7c8UB/ODgYOTm5jZY7sLCwgZvTqtr1KhR2LNnDzZt2oSTJ0/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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_all_features(df_20_3)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "Empty DataFrame\nColumns: [OberirdischeWohnflaeche, 1Stockflaeche, 2Stockflaeche, GeringequalitaetFlaeche, OberirdischeRaueme, Funktionalitaet, OberirdischeVollbadezimmer, OberirdischeHalbbadezimmer, Schlafzimmer, Kuechen, KuechenQualitaet, Kamine, Kaminqualitaet, Heizung, Heizungsqualitaet, Klimalanlage, Elektrik, Holzdeckflaeche, OffeneVerandaflaeche, GeschlosseneVerandaflaeche, Verkaufspreis]\nIndex: []",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>GeringequalitaetFlaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>Funktionalitaet</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>KuechenQualitaet</th>\n      <th>Kamine</th>\n      <th>Kaminqualitaet</th>\n      <th>Heizung</th>\n      <th>Heizungsqualitaet</th>\n      <th>Klimalanlage</th>\n      <th>Elektrik</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_20_3[df_20_3['OberirdischeWohnflaeche'].isnull()]"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [],
   "source": [
    "def drawbox_all(df):\n",
    "    plt.figure(figsize=(20, 20))\n",
    "    # get only numeric features\n",
    "    df = df.select_dtypes(include=['float64', 'int64'])\n",
    "    for i, feature in enumerate(df.columns):\n",
    "        # delete empty values\n",
    "        df = df[df[feature].notnull()]\n",
    "        try:\n",
    "            plt.subplot(5, 4, i+1)\n",
    "            plt.boxplot(df[feature])\n",
    "            plt.xlabel(feature)\n",
    "        except Exception as e:\n",
    "            print(e)\n",
    "    plt.show()\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 2000x2000 with 14 Axes>",
      "image/png": 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n1TdQ1Hh5eUuSPv98k9V7QZJycnK0eXOEVTsAAAAAAFAwNtt8XZJKly6t6dOn3zLWuHFjffrpp7bsHgBgA59//rm+/fZb/fOf/5QkXblyRUOGDNGjjz6qN998U6tXr9Yzzzyjbdu2qWTJkoqPj1dYWJgmTpyounXravLkyQoNDdV7770nSVq6dKkiIiI0d+5cZWVladSoUfLy8tLgwYMlSaGhobp69arWrFmjuLg4jR07VjVq1FDjxo3z7BsoiipUqChJ2r59m/r2fVzVq9eQxZIjw3DS8ePHtH37Nqt2AAAAAACgYCyGUbS34E1JSWMTYTgci0Xy9i7N+ITDyh2jBZWamqquXbvKx8dHtWrV0ptvvqlPPvlECxYsUGRkpCwWiwzD0COPPKJnn31W3bt316uvvionJye9+eabkqTTp0+rTZs22rZtm6pUqaLWrVtrxIgR6t69uyTps88+0zvvvKOvvvpKiYmJevjhh7V9+3ZVrlxZkhQWFqbs7Ox89V0QvF/hKLKzsxUc7K/09HQlJ5+7Ke7jU14eHiUVHb1Hzs7OdsgQ+J8/Op8AAAAAgD3ZdCktAMDfy7Rp09S1a1fVqlXLPBYXF6fAwEBZLBZJksViUZMmTRQbG2vGg4KCzPYVKlRQxYoVFRcXp7Nnz+r06dNq2rSpGQ8MDNQvv/yic+fOKS4uThUqVDCLIrnxPXv25KtvoChydnZW/foNb1kUkaTk5HOqX78BRREAAAAAAP4gmy6lBQD4+9i5c6d++uknbdq0SeHh4ebx5ORkq0KJJHl5eSkhIUGSdO7cOZUvX/6m+JkzZ5ScnCxJVnFv7+v7JuTGb3Xu2bNn89V3Qfy3tgLYXWZmprZu3SxJ5p1QuXJfb926WdeuZcrV1dVeaQKS+OwEAAAAUDRRGAEA5CkjI0MTJkzQ+PHj5e7ubhVLT0+/6ctZV1dXZWZmSpKuXr162/jVq1fN1zfGpOtfDud17bziBeHlxVIwcAwzZ840N113c3Mz3yc3vs7JydHq1cs0cuRIe6UJAAAAAECRRWEEAJCnuXPnqmHDhmrVqtVNMTc3t5sKEZmZmWYB5XZxDw8PqyKIm5ub+VySPDw8/vC1f1+8yY/z59ljBI5h+/avzeetWj2odu3ay8ennJKTLygycqu2bfvSbNe//xB7pQlIun7HCIVlAAAAAEUNhREAQJ4+//xzpaSkKCAgQNL/ihdffvmlQkJClJKSYtU+JSXFXALL19f3lnEfHx/5+vpKur4kVu4+IrnLa+XGb3funa79++W38sMwRGEEDuG3336TdP09cPDgAbMQIklVqlSVt7e3UlJS9NtvvzFmAQAAAAD4A9h8HQCQpw8//FCbNm3Shg0btGHDBrVt21Zt27bVhg0b5Ofnpz179pj7IBiGod27d8vPz0+S5Ofnp5iYGPNap0+f1unTp+Xn5ydfX19VrFjRKh4TE6OKFSuqfPny8vf31y+//KIzZ85Yxf39/c1r36lvoCjy9r5e+EtOTlbduvW0eXOk0tLStHlzpOrWrWcWA3PbAQAAAACAguGOEaCQZWdnKzp6h65cuaiSJe9ScPD9cnZ2tndawJ9SqVIlq9elSpWSJFWrVk1eXl6aOXOmJk+erCeeeEIfffSR0tPT1bFjR0lS79691bdvX/n7+6tRo0aaPHmyWrdurSpVqpjxt956S/fcc4+k6/srDBo0SJJUpUoVtWzZUqNGjVJYWJj27t2riIgIrVy5UpLUoUOHO/YNFEWVK1cxn+/Zs1v79/+sxo3raf/+n7Vnz+5btgMAAAAAAPlHYQQoRBERGxUeHqbExBPmsapVqyk8fLJCQrrYMTPAdjw9PfXee+9pwoQJ+vjjj1WnTh0tWrRIJUuWlCQFBATo9ddf15w5c3Tx4kW1aNFCkyZNMs8fPHiwzp8/r2HDhsnZ2Vk9e/bUgAEDzPj06dMVFhamXr16ycfHR1OmTFHjxo3z1TdQFHl5eZnPU1KSNXLkCxo58oU7tgMAAAAAAPlnMYyivTp1Sgqb5cIxRERs1ODBfdW+fQe9+OJItWwZrO+/j9bs2TO1desWLV78IcUROAyLRfL2ZrPcGzGfwFF88skaPf/803m2mz//ffXs+fhfkBFwe8wnAAAAAIoi9hgBCkF2drbCw8PUvn0HLV++WkFBzeTp6amgoGZavny12rfvoPDwscrOzrZ3qgAAB1ehQsVCbQcAAAAAAKxRGAEKQVTUDiUmntALL4yUk5P128rJyUkjRrysxMTjioraYacMAQBFRZMmQeZzNzc3q9iNr29sBwAAAAAA8o/CCFAIzp49I0mqW7f+LeP16tW3agcAwO0sW/ZBobYDAAAAAADWKIwAhcDX9x5J0sGD+28ZP3Bgv1U7AABuJzp6p/n89/ve3Pj6xnYAAAAAACD/KIwAhaB58/tVtWo1vfPOTOXk5FjFcnJyNGfO26patbqaN7/fThkCAIqKkiVLSZJKlSqlzMwMq1hmZoZKlSpl1Q4AAAAAABSMi70TAP4OnJ2dFR4+WYMH91W/fk+obdt28vEpp+TkC/rqq0ht2/alFi/+UM7OzvZOFQDg4OrXbyhpjX777TeVKOGqRx/tqpYt79P33+/Upk2f6bfffruhHQAAAAAAKCgKI0AhCQnpouefH6GFC+dq69Yt5nFnZxc9//wIhYR0sWN2AICi4u677zafX7uWqfXr12r9+rV3bAcAAAAAAPKPwghQSCIiNmr+/Dl6+OFH9NBD7eTjc7eSk3/V9u2Rmj9/jgIDm1IcAQDk6csvv8h3uz59+to4GwAAAAAA/n4ojACFIDs7W+HhYWrfvoOWL18tZ2cneXuXVkpKmvr3f0r9+/dWePhYdezYmeW0AAB3dPny5UJtBwAAAAAArLH5OlAIoqJ2KDHxhF54YaScnKzfVk5OThox4mUlJh5XVNQOO2UIACgq3N09CrUdAAAAAACwRmEEKARnz56RJNWtW/+W8Xr16lu1AwDgdtLSLhVqOwAAAAAAYI3CCFAIfH3vkSQdPLj/lvEDB/ZbtQMA4HZ+/nlfobYDAAAAAADWKIwAhaB58/tVtWo1vfPOTOXk5FjFcnJyNGfO26patbqaN7/fThkCAIqKnJzsQm0HAAAAAACsURgBCoGzs7PCwydr69Yt6t+/t3btilZaWpp27YpW//69tXXrFoWHv8HG6wCAPJUq5Vmo7QAAAAAAgDUKI0AhCQnposWLP9SBA/vVqdPDKlOmjDp1elgHDhzQ4sUfKiSki71TBAAUAVWrVi3UdgAAAAAAwJqLvRMA/k5CQrqoY8fOio7eoStXLqpkybsUHHw/d4oAAPKtUqUq+umnXflqBwAAAAAACo7CCFDInJ2d1aJFK3l7l1ZKSpoMw94ZAQCKkqSkpEJtBwAAAAAArLGUFgAAgANJSjpRqO0AAAAAAIA1CiMAAAAOJb+3GnJLIgAAAAAAfwSFEQAAAAfi5eVdqO0AAAAAAIA1CiMAAAAOJDk5uVDbAQAAAAAAaxRGAAAAHEh6enqhtgMAAAAAANYojAAAADgU9hgBAAAAAMCWKIwAAAA4kKysrEJtBwAAAAAArFEYAQAAcCCZmZmF2g4AAAAAAFijMAIAAAAAAAAAAIoNCiMAgHw7ceKEBg8erICAALVu3VoffPCBGUtKStKAAQPk7++vTp066fvvv7c6d8eOHQoJCZGfn5/69eunpKQkq/iyZcvUqlUrBQQEaMyYMVYbS2dkZGjMmDEKCgpSy5YttWTJEqtz8+obKErc3T0KtR0AAAAAALBGYQQAkC85OTkaMmSIypUrp08//VQTJ07UggULtGnTJhmGoaFDh8rb21vr1q1T165dNWzYMJ06dUqSdOrUKQ0dOlTdu3fXJ598orvvvlvPP/+8DOP65tFffvml5s6dq9dff13Lly9XXFycZsyYYfY9ffp07du3T8uXL9eECRM0d+5cbdmyRZLy7BsoaoKCmhZqOwAAAAAAYM3F3gkAAIqGlJQU1atXT+Hh4fL09FT16tV13333KSYmRt7e3kpKStJHH32kkiVLqmbNmtq5c6fWrVun4cOHa+3atWrYsKEGDRokSZo6dapatGihH3/8UcHBwVqxYoX69++vNm3aSJImTpyowYMHa9SoUTIMQ2vXrtX777+vBg0aqEGDBkpISNCqVavUoUMHRUVF3bFvoKg5cODnQm0HAAAAAACscccIACBfypcvr9mzZ8vT01OGYSgmJka7du1Ss2bNFBcXp/r166tkyZJm+8DAQMXGxkqS4uLiFBQUZMY8PDzUoEEDxcbGKjs7W3v37rWK+/v769q1azp48KAOHjyorKwsBQQEWF07Li5OOTk5efYNFDWpqamF2g4AAAAAAFjjjhEAQIG1bdtWp06dUps2bfTII49oypQpKl++vFUbLy8vnTlzRpKUnJx82/ilS5eUkZFhFXdxcVHZsmV15swZOTk5qVy5cnJ1dTXj3t7eysjIUGpq6h2vXRAWS4GaAzZjyedgtFgsjFvYHWMQAAAAQFH0lxVGhgwZorvvvltvvvmmJGn//v2aMGGC/vOf/6hWrVqaOHGiGjZs+FelAwD4E+bMmaOUlBSFh4dr6tSpSk9PtypcSJKrq6syMzMl6Y7xq1evmq9vFTcM45YxScrMzMyz7/zy8ipdoPaArRSkMOLtzbgFAAAAAKCg/pLCyOeff65vv/1W//znPyVJV65c0ZAhQ/Too4/qzTff1OrVq/XMM89o27ZtVkuhAAAcU6NGjSRJGRkZeuWVV9SjRw+lp6dbtcnMzJS7u7skyc3N7aZCRWZmpsqUKSM3Nzfz9e/jHh4eys7OvmVMktzd3eXm5nbTkkI39p1f58+n6b97wQN2lZOTk+92KSlpNs4GuDOLhcIyAAAAgKLH5nuMpKamavr06eaXaJL0xRdfyM3NTa+++qpq1qypsLAwlSpVSlu2bLF1OgCAPyglJUWRkZFWx2rVqqVr167Jx8dHKSkpN7XPXeLK19f3lnE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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawbox_all(df_20_3)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Correlation of features"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [],
   "source": [
    "def calculate_correlation(df):\n",
    "    df = df.select_dtypes(include=['float64', 'int64'])\n",
    "    corr = df.corr()\n",
    "    corr.style.background_gradient(cmap='coolwarm')\n",
    "    return corr"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "data": {
      "text/plain": "                            OberirdischeWohnflaeche  1Stockflaeche  \\\nOberirdischeWohnflaeche                    1.000000       0.565485   \n1Stockflaeche                              0.565485       1.000000   \n2Stockflaeche                              0.656143      -0.244670   \nGeringequalitaetFlaeche                    0.106391      -0.007187   \nOberirdischeRaueme                         0.804733       0.392793   \nOberirdischeVollbadezimmer                 0.631628       0.355478   \nOberirdischeHalbbadezimmer                 0.439814      -0.093701   \nSchlafzimmer                               0.511008       0.097086   \nKuechen                                    0.105425       0.057374   \nKamine                                     0.470407       0.417018   \nHolzdeckflaeche                            0.277855       0.242826   \nOffeneVerandaflaeche                       0.327014       0.246803   \nGeschlosseneVerandaflaeche                 0.003025      -0.056366   \nVerkaufspreis                              0.709304       0.613999   \n\n                            2Stockflaeche  GeringequalitaetFlaeche  \\\nOberirdischeWohnflaeche          0.656143                 0.106391   \n1Stockflaeche                   -0.244670                -0.007187   \n2Stockflaeche                    1.000000                 0.021460   \nGeringequalitaetFlaeche          0.021460                 1.000000   \nOberirdischeRaueme               0.582492                 0.108784   \nOberirdischeVollbadezimmer       0.423569                -0.000858   \nOberirdischeHalbbadezimmer       0.613555                -0.054445   \nSchlafzimmer                     0.506908                 0.091945   \nKuechen                          0.071979                 0.004463   \nKamine                           0.176890                -0.009132   \nHolzdeckflaeche                  0.108537                -0.013051   \nOffeneVerandaflaeche             0.162578                -0.007466   \nGeschlosseneVerandaflaeche       0.042794                 0.111712   \nVerkaufspreis                    0.284522                -0.051831   \n\n                            OberirdischeRaueme  OberirdischeVollbadezimmer  \\\nOberirdischeWohnflaeche               0.804733                    0.631628   \n1Stockflaeche                         0.392793                    0.355478   \n2Stockflaeche                         0.582492                    0.423569   \nGeringequalitaetFlaeche               0.108784                   -0.000858   \nOberirdischeRaueme                    1.000000                    0.534220   \nOberirdischeVollbadezimmer            0.534220                    1.000000   \nOberirdischeHalbbadezimmer            0.346469                    0.195038   \nSchlafzimmer                          0.667741                    0.352806   \nKuechen                               0.270973                    0.171352   \nKamine                                0.334844                    0.258480   \nHolzdeckflaeche                       0.186048                    0.214551   \nOffeneVerandaflaeche                  0.232798                    0.256520   \nGeschlosseneVerandaflaeche            0.009081                   -0.108523   \nVerkaufspreis                         0.498022                    0.557413   \n\n                            OberirdischeHalbbadezimmer  Schlafzimmer  \\\nOberirdischeWohnflaeche                       0.439814      0.511008   \n1Stockflaeche                                -0.093701      0.097086   \n2Stockflaeche                                 0.613555      0.506908   \nGeringequalitaetFlaeche                      -0.054445      0.091945   \nOberirdischeRaueme                            0.346469      0.667741   \nOberirdischeVollbadezimmer                    0.195038      0.352806   \nOberirdischeHalbbadezimmer                    1.000000      0.251329   \nSchlafzimmer                                  0.251329      1.000000   \nKuechen                                      -0.049799      0.244024   \nKamine                                        0.213546      0.097466   \nHolzdeckflaeche                               0.125439      0.047439   \nOffeneVerandaflaeche                          0.191969      0.066012   \nGeschlosseneVerandaflaeche                   -0.085975      0.048434   \nVerkaufspreis                                 0.295941      0.156109   \n\n                             Kuechen    Kamine  Holzdeckflaeche  \\\nOberirdischeWohnflaeche     0.105425  0.470407         0.277855   \n1Stockflaeche               0.057374  0.417018         0.242826   \n2Stockflaeche               0.071979  0.176890         0.108537   \nGeringequalitaetFlaeche     0.004463 -0.009132        -0.013051   \nOberirdischeRaueme          0.270973  0.334844         0.186048   \nOberirdischeVollbadezimmer  0.171352  0.258480         0.214551   \nOberirdischeHalbbadezimmer -0.049799  0.213546         0.125439   \nSchlafzimmer                0.244024  0.097466         0.047439   \nKuechen                     1.000000 -0.118355        -0.097256   \nKamine                     -0.118355  1.000000         0.230258   \nHolzdeckflaeche            -0.097256  0.230258         1.000000   \nOffeneVerandaflaeche       -0.087708  0.162350         0.066171   \nGeschlosseneVerandaflaeche  0.022994  0.014935        -0.112709   \nVerkaufspreis              -0.131764  0.484715         0.357625   \n\n                            OffeneVerandaflaeche  GeschlosseneVerandaflaeche  \\\nOberirdischeWohnflaeche                 0.327014                    0.003025   \n1Stockflaeche                           0.246803                   -0.056366   \n2Stockflaeche                           0.162578                    0.042794   \nGeringequalitaetFlaeche                -0.007466                    0.111712   \nOberirdischeRaueme                      0.232798                    0.009081   \nOberirdischeVollbadezimmer              0.256520                   -0.108523   \nOberirdischeHalbbadezimmer              0.191969                   -0.085975   \nSchlafzimmer                            0.066012                    0.048434   \nKuechen                                -0.087708                    0.022994   \nKamine                                  0.162350                    0.014935   \nHolzdeckflaeche                         0.066171                   -0.112709   \nOffeneVerandaflaeche                    1.000000                   -0.074113   \nGeschlosseneVerandaflaeche             -0.074113                    1.000000   \nVerkaufspreis                           0.312011                   -0.121361   \n\n                            Verkaufspreis  \nOberirdischeWohnflaeche          0.709304  \n1Stockflaeche                    0.613999  \n2Stockflaeche                    0.284522  \nGeringequalitaetFlaeche         -0.051831  \nOberirdischeRaueme               0.498022  \nOberirdischeVollbadezimmer       0.557413  \nOberirdischeHalbbadezimmer       0.295941  \nSchlafzimmer                     0.156109  \nKuechen                         -0.131764  \nKamine                           0.484715  \nHolzdeckflaeche                  0.357625  \nOffeneVerandaflaeche             0.312011  \nGeschlosseneVerandaflaeche      -0.121361  \nVerkaufspreis                    1.000000  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>GeringequalitaetFlaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>Kamine</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>OberirdischeWohnflaeche</th>\n      <td>1.000000</td>\n      <td>0.565485</td>\n      <td>0.656143</td>\n      <td>0.106391</td>\n      <td>0.804733</td>\n      <td>0.631628</td>\n      <td>0.439814</td>\n      <td>0.511008</td>\n      <td>0.105425</td>\n      <td>0.470407</td>\n      <td>0.277855</td>\n      <td>0.327014</td>\n      <td>0.003025</td>\n      <td>0.709304</td>\n    </tr>\n    <tr>\n      <th>1Stockflaeche</th>\n      <td>0.565485</td>\n      <td>1.000000</td>\n      <td>-0.244670</td>\n      <td>-0.007187</td>\n      <td>0.392793</td>\n      <td>0.355478</td>\n      <td>-0.093701</td>\n      <td>0.097086</td>\n      <td>0.057374</td>\n      <td>0.417018</td>\n      <td>0.242826</td>\n      <td>0.246803</td>\n      <td>-0.056366</td>\n      <td>0.613999</td>\n    </tr>\n    <tr>\n      <th>2Stockflaeche</th>\n      <td>0.656143</td>\n      <td>-0.244670</td>\n      <td>1.000000</td>\n      <td>0.021460</td>\n      <td>0.582492</td>\n      <td>0.423569</td>\n      <td>0.613555</td>\n      <td>0.506908</td>\n      <td>0.071979</td>\n      <td>0.176890</td>\n      <td>0.108537</td>\n      <td>0.162578</td>\n      <td>0.042794</td>\n      <td>0.284522</td>\n    </tr>\n    <tr>\n      <th>GeringequalitaetFlaeche</th>\n      <td>0.106391</td>\n      <td>-0.007187</td>\n      <td>0.021460</td>\n      <td>1.000000</td>\n      <td>0.108784</td>\n      <td>-0.000858</td>\n      <td>-0.054445</td>\n      <td>0.091945</td>\n      <td>0.004463</td>\n      <td>-0.009132</td>\n      <td>-0.013051</td>\n      <td>-0.007466</td>\n      <td>0.111712</td>\n      <td>-0.051831</td>\n    </tr>\n    <tr>\n      <th>OberirdischeRaueme</th>\n      <td>0.804733</td>\n      <td>0.392793</td>\n      <td>0.582492</td>\n      <td>0.108784</td>\n      <td>1.000000</td>\n      <td>0.534220</td>\n      <td>0.346469</td>\n      <td>0.667741</td>\n      <td>0.270973</td>\n      <td>0.334844</td>\n      <td>0.186048</td>\n      <td>0.232798</td>\n      <td>0.009081</td>\n      <td>0.498022</td>\n    </tr>\n    <tr>\n      <th>OberirdischeVollbadezimmer</th>\n      <td>0.631628</td>\n      <td>0.355478</td>\n      <td>0.423569</td>\n      <td>-0.000858</td>\n      <td>0.534220</td>\n      <td>1.000000</td>\n      <td>0.195038</td>\n      <td>0.352806</td>\n      <td>0.171352</td>\n      <td>0.258480</td>\n      <td>0.214551</td>\n      <td>0.256520</td>\n      <td>-0.108523</td>\n      <td>0.557413</td>\n    </tr>\n    <tr>\n      <th>OberirdischeHalbbadezimmer</th>\n      <td>0.439814</td>\n      <td>-0.093701</td>\n      <td>0.613555</td>\n      <td>-0.054445</td>\n      <td>0.346469</td>\n      <td>0.195038</td>\n      <td>1.000000</td>\n      <td>0.251329</td>\n      <td>-0.049799</td>\n      <td>0.213546</td>\n      <td>0.125439</td>\n      <td>0.191969</td>\n      <td>-0.085975</td>\n      <td>0.295941</td>\n    </tr>\n    <tr>\n      <th>Schlafzimmer</th>\n      <td>0.511008</td>\n      <td>0.097086</td>\n      <td>0.506908</td>\n      <td>0.091945</td>\n      <td>0.667741</td>\n      <td>0.352806</td>\n      <td>0.251329</td>\n      <td>1.000000</td>\n      <td>0.244024</td>\n      <td>0.097466</td>\n      <td>0.047439</td>\n      <td>0.066012</td>\n      <td>0.048434</td>\n      <td>0.156109</td>\n    </tr>\n    <tr>\n      <th>Kuechen</th>\n      <td>0.105425</td>\n      <td>0.057374</td>\n      <td>0.071979</td>\n      <td>0.004463</td>\n      <td>0.270973</td>\n      <td>0.171352</td>\n      <td>-0.049799</td>\n      <td>0.244024</td>\n      <td>1.000000</td>\n      <td>-0.118355</td>\n      <td>-0.097256</td>\n      <td>-0.087708</td>\n      <td>0.022994</td>\n      <td>-0.131764</td>\n    </tr>\n    <tr>\n      <th>Kamine</th>\n      <td>0.470407</td>\n      <td>0.417018</td>\n      <td>0.176890</td>\n      <td>-0.009132</td>\n      <td>0.334844</td>\n      <td>0.258480</td>\n      <td>0.213546</td>\n      <td>0.097466</td>\n      <td>-0.118355</td>\n      <td>1.000000</td>\n      <td>0.230258</td>\n      <td>0.162350</td>\n      <td>0.014935</td>\n      <td>0.484715</td>\n    </tr>\n    <tr>\n      <th>Holzdeckflaeche</th>\n      <td>0.277855</td>\n      <td>0.242826</td>\n      <td>0.108537</td>\n      <td>-0.013051</td>\n      <td>0.186048</td>\n      <td>0.214551</td>\n      <td>0.125439</td>\n      <td>0.047439</td>\n      <td>-0.097256</td>\n      <td>0.230258</td>\n      <td>1.000000</td>\n      <td>0.066171</td>\n      <td>-0.112709</td>\n      <td>0.357625</td>\n    </tr>\n    <tr>\n      <th>OffeneVerandaflaeche</th>\n      <td>0.327014</td>\n      <td>0.246803</td>\n      <td>0.162578</td>\n      <td>-0.007466</td>\n      <td>0.232798</td>\n      <td>0.256520</td>\n      <td>0.191969</td>\n      <td>0.066012</td>\n      <td>-0.087708</td>\n      <td>0.162350</td>\n      <td>0.066171</td>\n      <td>1.000000</td>\n      <td>-0.074113</td>\n      <td>0.312011</td>\n    </tr>\n    <tr>\n      <th>GeschlosseneVerandaflaeche</th>\n      <td>0.003025</td>\n      <td>-0.056366</td>\n      <td>0.042794</td>\n      <td>0.111712</td>\n      <td>0.009081</td>\n      <td>-0.108523</td>\n      <td>-0.085975</td>\n      <td>0.048434</td>\n      <td>0.022994</td>\n      <td>0.014935</td>\n      <td>-0.112709</td>\n      <td>-0.074113</td>\n      <td>1.000000</td>\n      <td>-0.121361</td>\n    </tr>\n    <tr>\n      <th>Verkaufspreis</th>\n      <td>0.709304</td>\n      <td>0.613999</td>\n      <td>0.284522</td>\n      <td>-0.051831</td>\n      <td>0.498022</td>\n      <td>0.557413</td>\n      <td>0.295941</td>\n      <td>0.156109</td>\n      <td>-0.131764</td>\n      <td>0.484715</td>\n      <td>0.357625</td>\n      <td>0.312011</td>\n      <td>-0.121361</td>\n      <td>1.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calculate_correlation(df_20_3)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Correction of dataset\n",
    "- 1. Because Kamine = 0 for all 960 Values, set Kamniqualität = NA for all"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Kamine Kaminqualitaet\n",
      "Id                         \n",
      "1          0             NA\n",
      "2          0             NA\n",
      "3          1             Du\n",
      "4          1             Du\n",
      "5          2             Gu\n",
      "...      ...            ...\n",
      "1996       0             NA\n",
      "1997       2             Du\n",
      "1998       1             Gu\n",
      "1999       0             NA\n",
      "2000       1             Du\n",
      "\n",
      "[2000 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "df_20_3['Kaminqualitaet'] = df_20_3['Kaminqualitaet'].fillna('NA')\n",
    "\n",
    "selected_columns = ['Kamine','Kaminqualitaet']\n",
    "print(df_20_3.loc[:,selected_columns])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "- 2. Null values in other Features"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "outputs": [
    {
     "data": {
      "text/plain": "      OberirdischeWohnflaeche  1Stockflaeche  2Stockflaeche  \\\nId                                                            \n542                     65.97          65.97           0.00   \n1001                   133.56          77.94          45.36   \n\n      GeringequalitaetFlaeche  OberirdischeRaueme Funktionalitaet  \\\nId                                                                  \n542                      0.00                   4             NaN   \n1001                    10.26                   6             NaN   \n\n      OberirdischeVollbadezimmer  OberirdischeHalbbadezimmer  Schlafzimmer  \\\nId                                                                           \n542                            1                           0             2   \n1001                           2                           0             3   \n\n      Kuechen KuechenQualitaet  Kamine Kaminqualitaet Heizung  \\\nId                                                              \n542         1               Ar       0             NA  WandOf   \n1001        1               Du       0             NA   GasWO   \n\n     Heizungsqualitaet Klimalanlage Elektrik  Holzdeckflaeche  \\\nId                                                              \n542                 Sc            N   SichDu             0.00   \n1001                Ar            J    SLSRo             1.26   \n\n      OffeneVerandaflaeche  GeschlosseneVerandaflaeche  Verkaufspreis  \nId                                                                     \n542                   0.00                         0.0        11135.0  \n1001                 18.99                         0.0        42500.0  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>GeringequalitaetFlaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>Funktionalitaet</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>KuechenQualitaet</th>\n      <th>Kamine</th>\n      <th>Kaminqualitaet</th>\n      <th>Heizung</th>\n      <th>Heizungsqualitaet</th>\n      <th>Klimalanlage</th>\n      <th>Elektrik</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>542</th>\n      <td>65.97</td>\n      <td>65.97</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>4</td>\n      <td>NaN</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>WandOf</td>\n      <td>Sc</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>11135.0</td>\n    </tr>\n    <tr>\n      <th>1001</th>\n      <td>133.56</td>\n      <td>77.94</td>\n      <td>45.36</td>\n      <td>10.26</td>\n      <td>6</td>\n      <td>NaN</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWO</td>\n      <td>Ar</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>1.26</td>\n      <td>18.99</td>\n      <td>0.0</td>\n      <td>42500.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Funktionalität: 2 NaN (mit Kaminqualitaet NaN)\n",
    "df_20_3[df_20_3['Funktionalitaet'].isnull()]"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "outputs": [],
   "source": [
    "df_20_3['Funktionalitaet']=df_20_3['Funktionalitaet'].fillna(df_20_3['Funktionalitaet'].mode()[0])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "outputs": [
    {
     "data": {
      "text/plain": "OberirdischeWohnflaeche                133.56\n1Stockflaeche                           77.94\n2Stockflaeche                           45.36\nGeringequalitaetFlaeche                 10.26\nOberirdischeRaueme                          6\nFunktionalitaet                           Typ\nOberirdischeVollbadezimmer                  2\nOberirdischeHalbbadezimmer                  0\nSchlafzimmer                                3\nKuechen                                     1\nKuechenQualitaet                           Du\nKamine                                      0\nKaminqualitaet                             NA\nHeizung                                 GasWO\nHeizungsqualitaet                          Ar\nKlimalanlage                                J\nElektrik                                SLSRo\nHolzdeckflaeche                          1.26\nOffeneVerandaflaeche                    18.99\nGeschlosseneVerandaflaeche                0.0\nVerkaufspreis                         42500.0\nPreisklasse                   32500.0-52500.0\nName: 1001, dtype: object"
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_20_3.loc(axis=0)[542]\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "outputs": [],
   "source": [
    "#KuechenQualitaet: 1 NaN (mit Kaminqualitaet NaN)\n",
    "df_20_3[df_20_3['KuechenQualitaet'].isnull()]\n",
    "df_20_3['KuechenQualitaet']=df_20_3['KuechenQualitaet'].fillna(df_20_3['KuechenQualitaet'].mode()[0])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "outputs": [],
   "source": [
    "#Elektrik: 1 NaN (mit Kaminqualitaet NaN)\n",
    "df_20_3[df_20_3['Elektrik'].isnull()]\n",
    "df_20_3['Elektrik']=df_20_3['Elektrik'].fillna(df_20_3['Elektrik'].mode()[0])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "- 3. Delete Column GeringequalitaetFlaeche, because only 29 not 0"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "outputs": [],
   "source": [
    "df_20_3 = df_20_3.drop('GeringequalitaetFlaeche', axis=1)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "- 4. Delete 29 rows where Heizung != GasWO????  (join columns does not make sense)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "outputs": [
    {
     "data": {
      "text/plain": "      OberirdischeWohnflaeche  1Stockflaeche  2Stockflaeche  \\\nId                                                            \n1                       84.96          84.96           0.00   \n28                     137.61          97.92          39.69   \n63                     122.58          88.74          33.84   \n330                     71.01          71.01           0.00   \n350                    183.24         183.24           0.00   \n384                    104.76         104.76           0.00   \n391                    140.94          83.70          57.24   \n417                    136.53          89.73          46.80   \n526                    203.04         101.52         101.52   \n542                     65.97          65.97           0.00   \n587                    212.22          84.42         109.35   \n590                    237.60         118.80         118.80   \n680                    206.19         113.40          92.79   \n713                     93.60          93.60           0.00   \n740                     83.16          60.48          22.68   \n771                     62.37          62.37           0.00   \n801                    236.16         123.30         112.86   \n1055                   159.66          98.55          61.11   \n1102                    93.60          93.60           0.00   \n1226                   185.22         102.06          83.16   \n1338                   159.12          79.20          79.92   \n1464                    98.64          51.48          47.16   \n1548                   112.50          61.74          50.76   \n1559                   137.07          88.74          48.33   \n1567                    93.60          93.60           0.00   \n1736                    87.12          54.00          33.12   \n1813                   198.90         106.02          92.88   \n1824                    85.68          85.68           0.00   \n1919                    72.00          72.00           0.00   \n\n      OberirdischeRaueme Funktionalitaet  OberirdischeVollbadezimmer  \\\nId                                                                     \n1                      4            Ger1                           1   \n28                     9             Mit                           2   \n63                     7             Typ                           2   \n330                    5             Typ                           1   \n350                    8             Typ                           2   \n384                    5             Typ                           1   \n391                    7             Typ                           2   \n417                    7             Typ                           2   \n526                   12             Typ                           2   \n542                    4             NaN                           1   \n587                    8             Typ                           2   \n590                    8             Typ                           1   \n680                    9             Typ                           2   \n713                    6             Typ                           2   \n740                    5             Typ                           1   \n771                    4             Typ                           1   \n801                   10             Typ                           2   \n1055                   8            Ger2                           2   \n1102                   6             Typ                           2   \n1226                   8             Typ                           1   \n1338                   6             Typ                           1   \n1464                   5             Typ                           1   \n1548                   7             Typ                           1   \n1559                   7            Gro2                           2   \n1567                   6             Typ                           2   \n1736                   6             Typ                           1   \n1813                   8             Typ                           2   \n1824                   4             Typ                           1   \n1919                   4            Gro1                           1   \n\n      OberirdischeHalbbadezimmer  Schlafzimmer  Kuechen KuechenQualitaet  \\\nId                                                                         \n1                              0             2        1               Ar   \n28                             0             4        1               Du   \n63                             0             4        1               Du   \n330                            0             2        1               Du   \n350                            0             3        1               Du   \n384                            0             3        1               Du   \n391                            0             3        1               Gu   \n417                            0             3        1               Ar   \n526                            0             4        2               Ar   \n542                            0             2        1               Ar   \n587                            0             4        1               Du   \n590                            1             4        1               Gu   \n680                            0             4        2               Du   \n713                            0             2        2               Du   \n740                            0             2        1               Ar   \n771                            0             2        1               Ar   \n801                            1             4        1               Du   \n1055                           0             4        2               Du   \n1102                           0             2        2               Du   \n1226                           1             3        1               Du   \n1338                           1             2        1               Du   \n1464                           0             2        1               Du   \n1548                           1             3        1               Ar   \n1559                           0             3        1               Ar   \n1567                           0             2        2               Du   \n1736                           0             2        1               Du   \n1813                           0             5        1               Ar   \n1824                           0             2        1               Ar   \n1919                           0             1        1               Ar   \n\n      Kamine Kaminqualitaet Heizung Heizungsqualitaet Klimalanlage Elektrik  \\\nId                                                                            \n1          0             NA   GasWD                Ar            N   SichAr   \n28         0             NA  WandOf                Du            N   SichAr   \n63         0             NA   GasWD                Ar            N    SLSRo   \n330        0             NA  GravOf                Ar            N    SLSRo   \n350        2             Gu   GasWD                Du            J    SLSRo   \n384        0             NA   GasWD                Du            N    SLSRo   \n391        0             NA   GasWD                Du            N    SLSRo   \n417        0             NA   GasWD                Du            N   SichAr   \n526        0             NA  GravOf                Ar            N   SichAr   \n542        0             NA  WandOf                Sc            N   SichDu   \n587        0             NA  NGasWD                Ar            N    SLSRo   \n590        1             Gu   GasWD                Du            N    SLSRo   \n680        1             Gu   GasWD                Ag            N    SLSRo   \n713        0             NA  WandOf                Ar            N   SichAr   \n740        0             NA  GravOf                Ar            N   SichDu   \n771        0             NA  GravOf                Ar            N   SichDu   \n801        1             Gu   GasWD                Du            N   SichDu   \n1055       0             NA   GasWD                Ar            N    SLSRo   \n1102       0             NA  WandOf                Ar            N   SichAr   \n1226       1             Gu  NGasWD                Ar            N    SLSRo   \n1338       2             Du   GasWD                Ar            N    SLSRo   \n1464       0             NA  GravOf                Ar            N   SichAr   \n1548       0             NA   GasWD                Gu            J    SLSRo   \n1559       1             Du   GasWD                Ar            N    SLSRo   \n1567       0             NA  WandOf                Ar            N   SichDu   \n1736       0             NA  GravOf                Ar            N    SLSRo   \n1813       0             NA   GasWD                Du            J    SLSRo   \n1824       1             Gu  GravOf                Ar            N   SichAr   \n1919       1             Sc  GravOf                Ar            N   SichDu   \n\n      Holzdeckflaeche  OffeneVerandaflaeche  GeschlosseneVerandaflaeche  \\\nId                                                                        \n1                0.00                  0.00                        0.00   \n28               8.28                  0.00                       16.65   \n63               0.00                  0.00                        0.00   \n330              0.00                  0.00                       10.08   \n350              0.00                  0.00                        0.00   \n384              0.00                  4.32                        0.00   \n391              4.86                 20.52                       22.14   \n417              0.00                  0.00                       12.96   \n526              0.00                  1.62                        1.62   \n542              0.00                  0.00                        0.00   \n587              0.00                  4.86                        1.80   \n590             16.29                  0.00                       34.74   \n680              0.00                  0.00                        0.00   \n713              0.00                  0.00                        0.00   \n740              0.00                  0.00                        0.00   \n771              0.00                  1.80                        0.00   \n801              0.00                  0.00                        0.00   \n1055             0.00                  0.00                        8.10   \n1102             0.00                  0.00                        0.00   \n1226             0.00                  0.00                       23.31   \n1338             0.00                 30.69                        0.00   \n1464             0.00                  0.72                       11.52   \n1548            18.63                  0.00                        8.64   \n1559             0.00                  0.00                        7.29   \n1567             0.00                  0.00                        0.00   \n1736             0.00                  0.00                        0.00   \n1813             0.00                  4.32                        0.00   \n1824             0.00                  8.82                        0.00   \n1919             0.00                  0.00                        0.00   \n\n      Verkaufspreis  \nId                   \n1          69700.00  \n28         83300.00  \n63         81600.00  \n330        82025.00  \n350       318750.00  \n384       106250.00  \n391       127500.00  \n417        97750.00  \n526        65025.00  \n542        11135.00  \n587       103700.00  \n590       226082.15  \n680       113815.00  \n713        76500.00  \n740        68000.00  \n771        44625.00  \n801       203150.00  \n1055       73950.00  \n1102       69190.00  \n1226      110075.00  \n1338      138550.00  \n1464       67150.00  \n1548       98600.00  \n1559      134300.00  \n1567       74375.00  \n1736       32215.00  \n1813       99875.00  \n1824      102850.00  \n1919       51000.00  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>Funktionalitaet</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>KuechenQualitaet</th>\n      <th>Kamine</th>\n      <th>Kaminqualitaet</th>\n      <th>Heizung</th>\n      <th>Heizungsqualitaet</th>\n      <th>Klimalanlage</th>\n      <th>Elektrik</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>84.96</td>\n      <td>84.96</td>\n      <td>0.00</td>\n      <td>4</td>\n      <td>Ger1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>69700.00</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>137.61</td>\n      <td>97.92</td>\n      <td>39.69</td>\n      <td>9</td>\n      <td>Mit</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>WandOf</td>\n      <td>Du</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>8.28</td>\n      <td>0.00</td>\n      <td>16.65</td>\n      <td>83300.00</td>\n    </tr>\n    <tr>\n      <th>63</th>\n      <td>122.58</td>\n      <td>88.74</td>\n      <td>33.84</td>\n      <td>7</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>81600.00</td>\n    </tr>\n    <tr>\n      <th>330</th>\n      <td>71.01</td>\n      <td>71.01</td>\n      <td>0.00</td>\n      <td>5</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>10.08</td>\n      <td>82025.00</td>\n    </tr>\n    <tr>\n      <th>350</th>\n      <td>183.24</td>\n      <td>183.24</td>\n      <td>0.00</td>\n      <td>8</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>2</td>\n      <td>Gu</td>\n      <td>GasWD</td>\n      <td>Du</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>318750.00</td>\n    </tr>\n    <tr>\n      <th>384</th>\n      <td>104.76</td>\n      <td>104.76</td>\n      <td>0.00</td>\n      <td>5</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Du</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>4.32</td>\n      <td>0.00</td>\n      <td>106250.00</td>\n    </tr>\n    <tr>\n      <th>391</th>\n      <td>140.94</td>\n      <td>83.70</td>\n      <td>57.24</td>\n      <td>7</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Du</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>4.86</td>\n      <td>20.52</td>\n      <td>22.14</td>\n      <td>127500.00</td>\n    </tr>\n    <tr>\n      <th>417</th>\n      <td>136.53</td>\n      <td>89.73</td>\n      <td>46.80</td>\n      <td>7</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Du</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>12.96</td>\n      <td>97750.00</td>\n    </tr>\n    <tr>\n      <th>526</th>\n      <td>203.04</td>\n      <td>101.52</td>\n      <td>101.52</td>\n      <td>12</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>2</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>0.00</td>\n      <td>1.62</td>\n      <td>1.62</td>\n      <td>65025.00</td>\n    </tr>\n    <tr>\n      <th>542</th>\n      <td>65.97</td>\n      <td>65.97</td>\n      <td>0.00</td>\n      <td>4</td>\n      <td>NaN</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>WandOf</td>\n      <td>Sc</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>11135.00</td>\n    </tr>\n    <tr>\n      <th>587</th>\n      <td>212.22</td>\n      <td>84.42</td>\n      <td>109.35</td>\n      <td>8</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>NGasWD</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>4.86</td>\n      <td>1.80</td>\n      <td>103700.00</td>\n    </tr>\n    <tr>\n      <th>590</th>\n      <td>237.60</td>\n      <td>118.80</td>\n      <td>118.80</td>\n      <td>8</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>GasWD</td>\n      <td>Du</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>16.29</td>\n      <td>0.00</td>\n      <td>34.74</td>\n      <td>226082.15</td>\n    </tr>\n    <tr>\n      <th>680</th>\n      <td>206.19</td>\n      <td>113.40</td>\n      <td>92.79</td>\n      <td>9</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>2</td>\n      <td>Du</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>GasWD</td>\n      <td>Ag</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>113815.00</td>\n    </tr>\n    <tr>\n      <th>713</th>\n      <td>93.60</td>\n      <td>93.60</td>\n      <td>0.00</td>\n      <td>6</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>2</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>WandOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>76500.00</td>\n    </tr>\n    <tr>\n      <th>740</th>\n      <td>83.16</td>\n      <td>60.48</td>\n      <td>22.68</td>\n      <td>5</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>68000.00</td>\n    </tr>\n    <tr>\n      <th>771</th>\n      <td>62.37</td>\n      <td>62.37</td>\n      <td>0.00</td>\n      <td>4</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>1.80</td>\n      <td>0.00</td>\n      <td>44625.00</td>\n    </tr>\n    <tr>\n      <th>801</th>\n      <td>236.16</td>\n      <td>123.30</td>\n      <td>112.86</td>\n      <td>10</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>GasWD</td>\n      <td>Du</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>203150.00</td>\n    </tr>\n    <tr>\n      <th>1055</th>\n      <td>159.66</td>\n      <td>98.55</td>\n      <td>61.11</td>\n      <td>8</td>\n      <td>Ger2</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>2</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>8.10</td>\n      <td>73950.00</td>\n    </tr>\n    <tr>\n      <th>1102</th>\n      <td>93.60</td>\n      <td>93.60</td>\n      <td>0.00</td>\n      <td>6</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>2</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>WandOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>69190.00</td>\n    </tr>\n    <tr>\n      <th>1226</th>\n      <td>185.22</td>\n      <td>102.06</td>\n      <td>83.16</td>\n      <td>8</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>NGasWD</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>23.31</td>\n      <td>110075.00</td>\n    </tr>\n    <tr>\n      <th>1338</th>\n      <td>159.12</td>\n      <td>79.20</td>\n      <td>79.92</td>\n      <td>6</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>2</td>\n      <td>Du</td>\n      <td>GasWD</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>30.69</td>\n      <td>0.00</td>\n      <td>138550.00</td>\n    </tr>\n    <tr>\n      <th>1464</th>\n      <td>98.64</td>\n      <td>51.48</td>\n      <td>47.16</td>\n      <td>5</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>0.00</td>\n      <td>0.72</td>\n      <td>11.52</td>\n      <td>67150.00</td>\n    </tr>\n    <tr>\n      <th>1548</th>\n      <td>112.50</td>\n      <td>61.74</td>\n      <td>50.76</td>\n      <td>7</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Gu</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>18.63</td>\n      <td>0.00</td>\n      <td>8.64</td>\n      <td>98600.00</td>\n    </tr>\n    <tr>\n      <th>1559</th>\n      <td>137.07</td>\n      <td>88.74</td>\n      <td>48.33</td>\n      <td>7</td>\n      <td>Gro2</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>GasWD</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>7.29</td>\n      <td>134300.00</td>\n    </tr>\n    <tr>\n      <th>1567</th>\n      <td>93.60</td>\n      <td>93.60</td>\n      <td>0.00</td>\n      <td>6</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>2</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>WandOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>74375.00</td>\n    </tr>\n    <tr>\n      <th>1736</th>\n      <td>87.12</td>\n      <td>54.00</td>\n      <td>33.12</td>\n      <td>6</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>32215.00</td>\n    </tr>\n    <tr>\n      <th>1813</th>\n      <td>198.90</td>\n      <td>106.02</td>\n      <td>92.88</td>\n      <td>8</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>5</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWD</td>\n      <td>Du</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>0.00</td>\n      <td>4.32</td>\n      <td>0.00</td>\n      <td>99875.00</td>\n    </tr>\n    <tr>\n      <th>1824</th>\n      <td>85.68</td>\n      <td>85.68</td>\n      <td>0.00</td>\n      <td>4</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichAr</td>\n      <td>0.00</td>\n      <td>8.82</td>\n      <td>0.00</td>\n      <td>102850.00</td>\n    </tr>\n    <tr>\n      <th>1919</th>\n      <td>72.00</td>\n      <td>72.00</td>\n      <td>0.00</td>\n      <td>4</td>\n      <td>Gro1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>Ar</td>\n      <td>1</td>\n      <td>Sc</td>\n      <td>GravOf</td>\n      <td>Ar</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>51000.00</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_20_3[df_20_3['Heizung'] != 'GasWO']"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "- PCA–Reduktion:  Holzdeckflaeche, OffeneVerandaflaeche, GeschlosseneVerandaflaeche"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "outputs": [
    {
     "data": {
      "text/plain": "    OberirdischeWohnflaeche  1Stockflaeche  2Stockflaeche  OberirdischeRaueme  \\\nId                                                                              \n35                   122.04         122.04            0.0                   6   \n\n   Funktionalitaet  OberirdischeVollbadezimmer  OberirdischeHalbbadezimmer  \\\nId                                                                           \n35             Typ                           2                           0   \n\n    Schlafzimmer  Kuechen KuechenQualitaet  Kamine Kaminqualitaet Heizung  \\\nId                                                                          \n35             3        1               Du       1             Du   GasWO   \n\n   Heizungsqualitaet Klimalanlage Elektrik  Holzdeckflaeche  \\\nId                                                            \n35                Du            J    SLSRo           128.16   \n\n    OffeneVerandaflaeche  GeschlosseneVerandaflaeche  Verkaufspreis  \nId                                                                   \n35                   0.0                         0.0       159800.0  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>Funktionalitaet</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>KuechenQualitaet</th>\n      <th>Kamine</th>\n      <th>Kaminqualitaet</th>\n      <th>Heizung</th>\n      <th>Heizungsqualitaet</th>\n      <th>Klimalanlage</th>\n      <th>Elektrik</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>35</th>\n      <td>122.04</td>\n      <td>122.04</td>\n      <td>0.0</td>\n      <td>6</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>GasWO</td>\n      <td>Du</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>128.16</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>159800.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#One datapoint above 80\n",
    "df_20_3[df_20_3['Holzdeckflaeche'] > 80]"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "outputs": [
    {
     "data": {
      "text/plain": "      OberirdischeWohnflaeche  1Stockflaeche  2Stockflaeche  \\\nId                                                            \n701                    458.55         458.55           0.00   \n867                    238.86         141.03          97.83   \n1929                    64.80          64.80           0.00   \n\n      OberirdischeRaueme Funktionalitaet  OberirdischeVollbadezimmer  \\\nId                                                                     \n701                   15             Typ                           2   \n867                   11             Mit                           3   \n1929                   4             Typ                           1   \n\n      OberirdischeHalbbadezimmer  Schlafzimmer  Kuechen KuechenQualitaet  \\\nId                                                                         \n701                            1             2        1               Ag   \n867                            0             4        1               Du   \n1929                           0             2        1               Du   \n\n      Kamine Kaminqualitaet Heizung Heizungsqualitaet Klimalanlage Elektrik  \\\nId                                                                            \n701        2             Gu   GasWO                Ag            J    SLSRo   \n867        1             Gu   GasWO                Ar            J    SLSRo   \n1929       0             NA   GasWO                Du            N   SichDu   \n\n      Holzdeckflaeche  OffeneVerandaflaeche  GeschlosseneVerandaflaeche  \\\nId                                                                        \n701             49.14                 43.56                        0.00   \n867             11.52                 51.30                        0.00   \n1929             0.00                 47.07                       10.35   \n\n      Verkaufspreis  \nId                   \n701        156272.5  \n867        134300.0  \n1929        29665.0  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>Funktionalitaet</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>KuechenQualitaet</th>\n      <th>Kamine</th>\n      <th>Kaminqualitaet</th>\n      <th>Heizung</th>\n      <th>Heizungsqualitaet</th>\n      <th>Klimalanlage</th>\n      <th>Elektrik</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>701</th>\n      <td>458.55</td>\n      <td>458.55</td>\n      <td>0.00</td>\n      <td>15</td>\n      <td>Typ</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Ag</td>\n      <td>2</td>\n      <td>Gu</td>\n      <td>GasWO</td>\n      <td>Ag</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>49.14</td>\n      <td>43.56</td>\n      <td>0.00</td>\n      <td>156272.5</td>\n    </tr>\n    <tr>\n      <th>867</th>\n      <td>238.86</td>\n      <td>141.03</td>\n      <td>97.83</td>\n      <td>11</td>\n      <td>Mit</td>\n      <td>3</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>GasWO</td>\n      <td>Ar</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>11.52</td>\n      <td>51.30</td>\n      <td>0.00</td>\n      <td>134300.0</td>\n    </tr>\n    <tr>\n      <th>1929</th>\n      <td>64.80</td>\n      <td>64.80</td>\n      <td>0.00</td>\n      <td>4</td>\n      <td>Typ</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>Du</td>\n      <td>0</td>\n      <td>NA</td>\n      <td>GasWO</td>\n      <td>Du</td>\n      <td>N</td>\n      <td>SichDu</td>\n      <td>0.00</td>\n      <td>47.07</td>\n      <td>10.35</td>\n      <td>29665.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#One datapoint above 80\n",
    "df_20_3[df_20_3['OffeneVerandaflaeche'] > 40]"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "outputs": [
    {
     "data": {
      "text/plain": "      OberirdischeWohnflaeche  1Stockflaeche  2Stockflaeche  \\\nId                                                            \n1075                   163.98          99.45          64.53   \n\n      OberirdischeRaueme Funktionalitaet  OberirdischeVollbadezimmer  \\\nId                                                                     \n1075                   7            Ger2                           2   \n\n      OberirdischeHalbbadezimmer  Schlafzimmer  Kuechen KuechenQualitaet  \\\nId                                                                         \n1075                           0             4        1               Gu   \n\n      Kamine Kaminqualitaet Heizung Heizungsqualitaet Klimalanlage Elektrik  \\\nId                                                                            \n1075       1             Sc   GasWO                Ag            J    SLSRo   \n\n      Holzdeckflaeche  OffeneVerandaflaeche  GeschlosseneVerandaflaeche  \\\nId                                                                        \n1075              0.0                 17.55                       91.08   \n\n      Verkaufspreis  \nId                   \n1075       194225.0  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>OberirdischeWohnflaeche</th>\n      <th>1Stockflaeche</th>\n      <th>2Stockflaeche</th>\n      <th>OberirdischeRaueme</th>\n      <th>Funktionalitaet</th>\n      <th>OberirdischeVollbadezimmer</th>\n      <th>OberirdischeHalbbadezimmer</th>\n      <th>Schlafzimmer</th>\n      <th>Kuechen</th>\n      <th>KuechenQualitaet</th>\n      <th>Kamine</th>\n      <th>Kaminqualitaet</th>\n      <th>Heizung</th>\n      <th>Heizungsqualitaet</th>\n      <th>Klimalanlage</th>\n      <th>Elektrik</th>\n      <th>Holzdeckflaeche</th>\n      <th>OffeneVerandaflaeche</th>\n      <th>GeschlosseneVerandaflaeche</th>\n      <th>Verkaufspreis</th>\n    </tr>\n    <tr>\n      <th>Id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1075</th>\n      <td>163.98</td>\n      <td>99.45</td>\n      <td>64.53</td>\n      <td>7</td>\n      <td>Ger2</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>Gu</td>\n      <td>1</td>\n      <td>Sc</td>\n      <td>GasWO</td>\n      <td>Ag</td>\n      <td>J</td>\n      <td>SLSRo</td>\n      <td>0.0</td>\n      <td>17.55</td>\n      <td>91.08</td>\n      <td>194225.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#One datapoint above 80\n",
    "df_20_3[df_20_3['GeschlosseneVerandaflaeche'] > 60]"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  }
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